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ORCID38th NeurIPS 2024: Vancouver, BC, Canada
- Amir Globersons, Lester Mackey, Danielle Belgrave, Angela Fan, Ulrich Paquet, Jakub M. Tomczak, Cheng Zhang:
Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024. 2024 - Ionut-Vlad Modoranu, Mher Safaryan, Grigory Malinovsky, Eldar Kurtic, Thomas Robert, Peter Richtárik, Dan Alistarh:
MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence. - Yanbin Wei, Shuai Fu, Weisen Jiang, Zejian Zhang, Zhixiong Zeng, Qi Wu, James T. Kwok, Yu Zhang:
GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoning. - Changhoon Song, Yesom Park, Myungjoo Kang:
How does PDE order affect the convergence of PINNs? - Zikai Xiong, Niccolò Dalmasso, Shubham Sharma, Freddy Lécué, Daniele Magazzeni, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Fair Wasserstein Coresets. - Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang:
Improved Regret for Bandit Convex Optimization with Delayed Feedback. - Tomas Rigaux, Hisashi Kashima:
Enhancing Chess Reinforcement Learning with Graph Representation. - Ying Cheng, Yang Li, Junjie He, Rui Feng:
Mixtures of Experts for Audio-Visual Learning. - Markus Pettersen, Frederik Rogge, Mikkel E. Lepperød:
Learning Place Cell Representations and Context-Dependent Remapping. - Chih-Hung Liu, Gleb Novikov:
Robust Sparse Regression with Non-Isotropic Designs. - Hancheng Ye, Jiakang Yuan, Renqiu Xia, Xiangchao Yan, Tao Chen, Junchi Yan, Botian Shi, Bo Zhang:
Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy. - Xuan Zhang, Chao Du, Tianyu Pang, Qian Liu, Wei Gao, Min Lin:
Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs. - Shangzi Xue, Zhenya Huang, Jiayu Liu, Xin Lin, Yuting Ning, Binbin Jin, Xin Li, Qi Liu:
Decompose, Analyze and Rethink: Solving Intricate Problems with Human-like Reasoning Cycle. - Jiesong Liu, Feng Zhang, Jiawei Guan, Xipeng Shen:
UQ-Guided Hyperparameter Optimization for Iterative Learners. - Audrey Huang, Nan Jiang:
Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality. - Yuxuan Wang, Haixu Wu, Jiaxiang Dong, Guo Qin, Haoran Zhang, Yong Liu, Yunzhong Qiu, Jianmin Wang, Mingsheng Long:
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables. - Mohamed Elrefaie, Florin Morar, Angela Dai, Faez Ahmed:
DrivAerNet++: A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks. - Yuxuan Duan, Yan Hong, Bo Zhang, Jun Lan, Huijia Zhu, Weiqiang Wang, Jianfu Zhang, Li Niu, Liqing Zhang:
DomainGallery: Few-shot Domain-driven Image Generation by Attribute-centric Finetuning. - Weibo Gao, Qi Liu, Linan Yue, Fangzhou Yao, Hao Wang, Yin Gu, Zheng Zhang:
Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modeling. - Minghao Chen, Yihang Li, Yanting Yang, Shiyu Yu, Binbin Lin, Xiaofei He:
AutoManual: Constructing Instruction Manuals by LLM Agents via Interactive Environmental Learning. - Jiaqi Xu, Cuiling Lan, Wenxuan Xie, Xuejin Chen, Yan Lu:
Slot-VLM: Object-Event Slots for Video-Language Modeling. - Sicheng Xu, Guojun Chen, Yu-Xiao Guo, Jiaolong Yang, Chong Li, Zhenyu Zang, Yizhong Zhang, Xin Tong, Baining Guo:
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time. - Andrew Davison, S. Carlyle Morgan, Owen G. Ward:
Community Detection Guarantees using Embeddings Learned by Node2Vec. - Zijie Huang, Wanjia Zhao, Jingdong Gao, Ziniu Hu, Xiao Luo, Yadi Cao, Yuanzhou Chen, Yizhou Sun, Wei Wang:
Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling. - Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Tom Lieberum, Vikrant Varma, János Kramár, Rohin Shah, Neel Nanda:
Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders. - Xiaosong Jia, Zhenjie Yang, Qifeng Li, Zhiyuan Zhang, Junchi Yan:
Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving. - Gautham Vasan, Mohamed Elsayed, Seyed Alireza Azimi, Jiamin He, Fahim Shahriar, Colin Bellinger, Martha White, Rupam Mahmood:
Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers. - Ruifeng Ren, Yong Liu:
Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens. - Nicholas Babaev, Kirill Tamogashev, Azat Saginbaev, Ivan Shchekotov, Hanbin Bae, Hosang Sung, Won-Jun Lee, Hoon-Young Cho, Pavel Andreev:
FINALLY: fast and universal speech enhancement with studio-like quality. - Can Jin, Tong Che, Hongwu Peng, Yiyuan Li, Dimitris N. Metaxas, Marco Pavone:
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate. - Wuxuan Shi, Mang Ye:
Prospective Representation Learning for Non-Exemplar Class-Incremental Learning. - Matthew Macfarlane, Edan Toledo, Donal Byrne, Paul Duckworth, Alexandre Laterre:
SPO: Sequential Monte Carlo Policy Optimisation. - Jin Woo Lee, Jaehyun Park, Min Jun Choi, Kyogu Lee:
Differentiable Modal Synthesis for Physical Modeling of Planar String Sound and Motion Simulation. - Jiaqi Wang, Xiaochen Wang, Lingjuan Lyu, Jinghui Chen, Fenglong Ma:
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection. - Yu Zhang, Changhao Pan, Wenxiang Guo, Ruiqi Li, Zhiyuan Zhu, Jialei Wang, Wenhao Xu, Jingyu Lu, Zhiqing Hong, Chuxin Wang, Lichao Zhang, Jinzheng He, Ziyue Jiang, Yuxin Chen, Chen Yang, Jiecheng Zhou, Xinyu Cheng, Zhou Zhao:
GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks. - Yifan Li, Yikai Wang, Yanwei Fu, Dongyu Ru, Zheng Zhang, Tong He:
Unified Lexical Representation for Interpretable Visual-Language Alignment. - Andrea Amaduzzi, Pierluigi Zama Ramirez, Giuseppe Lisanti, Samuele Salti, Luigi Di Stefano:
LLaNA: Large Language and NeRF Assistant. - Zhihang Yuan, Hanling Zhang, Lu Pu, Xuefei Ning, Linfeng Zhang, Tianchen Zhao, Shengen Yan, Guohao Dai, Yu Wang:
DiTFastAttn: Attention Compression for Diffusion Transformer Models. - Vincent Hanke, Tom Blanchard, Franziska Boenisch, Iyiola E. Olatunji, Michael Backes, Adam Dziedzic:
Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives. - Kseniya Cherenkova, Elona Dupont, Anis Kacem, Gleb Gusev, Djamila Aouada:
SpelsNet: Surface Primitive Elements Segmentation by B-Rep Graph Structure Supervision. - Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, Michael W. Mahoney, Yakun Sophia Shao, Kurt Keutzer, Amir Gholami:
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization. - Weicai Ye, Chenhao Ji, Zheng Chen, Junyao Gao, Xiaoshui Huang, Song-Hai Zhang, Wanli Ouyang, Tong He, Cairong Zhao, Guofeng Zhang:
DiffPano: Scalable and Consistent Text to Panorama Generation with Spherical Epipolar-Aware Diffusion. - Mouad El Bouchattaoui, Myriam Tami, Benoit Lepetit, Paul-Henry Cournède:
Causal Contrastive Learning for Counterfactual Regression Over Time. - Weizhi Gao, Zhichao Hou, Han Xu, Xiaorui Liu:
Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing. - Sergio Hernan Garrido Mejia, Patrick Blöbaum, Bernhard Schölkopf, Dominik Janzing:
Causal vs. Anticausal merging of predictors. - Yanzhi Li, Keqiu Li, Li Guohui, Zumin Wang, Changqing Ji, Lubo Wang, Die Zuo, Qing Guo, Feng Zhang, Manyu Wang, Di Lin:
Sim2Real-Fire: A Multi-modal Simulation Dataset for Forecast and Backtracking of Real-world Forest Fire. - Dan Zhang, Ziniu Hu, Sining Zhoubian, Zhengxiao Du, Kaiyu Yang, Zihan Wang, Yisong Yue, Yuxiao Dong, Jie Tang:
SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models. - Zhilin Wang, Yi Dong, Olivier Delalleau, Jiaqi Zeng, Gerald Shen, Daniel Egert, Jimmy Zhang, Makesh Narsimhan Sreedhar, Oleksii Kuchaiev:
HelpSteer 2: Open-source dataset for training top-performing reward models. - Sophie Xhonneux, Alessandro Sordoni, Stephan Günnemann, Gauthier Gidel, Leo Schwinn:
Efficient Adversarial Training in LLMs with Continuous Attacks. - Zhu Yu, Runmin Zhang, Jiacheng Ying, Junchen Yu, Xiaohai Hu, Lun Luo, Si-Yuan Cao, Hui-Liang Shen:
Context and Geometry Aware Voxel Transformer for Semantic Scene Completion. - Quentin Leboutet, Nina Wiedemann, Zhipeng Cai, Michael Paulitsch, Kai Yuan:
MIDGArD: Modular Interpretable Diffusion over Graphs for Articulated Designs. - Samuel Teuber, Stefan Mitsch, André Platzer:
Provably Safe Neural Network Controllers via Differential Dynamic Logic. - Jason Hu, Bowen Song, Xiaojian Xu, Liyue Shen, Jeffrey A. Fessler:
Learning Image Priors Through Patch-Based Diffusion Models for Solving Inverse Problems. - Yangru Huang, Peixi Peng, Yifan Zhao, Guangyao Chen, Yonghong Tian:
Seek Commonality but Preserve Differences: Dissected Dynamics Modeling for Multi-modal Visual RL. - Julian Rodemann, Christoph Jansen, Georg Schollmeyer:
Reciprocal Learning. - Yikun Jiang, Huanyu Wang, Lei Xie, Hanbin Zhao, Zhang Chao, Hui Qian, John C. S. Lui:
D-LLM: A Token Adaptive Computing Resource Allocation Strategy for Large Language Models. - Pierre Clavier, Laixi Shi, Erwan Le Pennec, Eric Mazumdar, Adam Wierman, Matthieu Geist:
Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms. - Jun Xia, Shaorong Chen, Jingbo Zhou, Xiaojun Shan, Wenjie Du, Zhangyang Gao, Cheng Tan, Bozhen Hu, Jiangbin Zheng, Stan Z. Li:
AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases. - Zhenhui Ye, Tianyun Zhong, Yi Ren, Ziyue Jiang, Jiawei Huang, Rongjie Huang, Jinglin Liu, Jinzheng He, Chen Zhang, Zehan Wang, Xize Cheng, Xiang Yin, Zhou Zhao:
MimicTalk: Mimicking a personalized and expressive 3D talking face in minutes. - Kun Zhou, Beichen Zhang, Jiapeng Wang, Zhipeng Chen, Xin Zhao, Jing Sha, Zhichao Sheng, Shijin Wang, Ji-Rong Wen:
JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models. - Kun Yan, Zeyu Wang, Lei Ji, Yuntao Wang, Nan Duan, Shuai Ma:
Voila-A: Aligning Vision-Language Models with User's Gaze Attention. - Linus Ericsson, Miguel Espinosa, Chenhongyi Yang, Antreas Antoniou, Amos Storkey, Shay B. Cohen, Steven McDonagh, Elliot J. Crowley:
einspace: Searching for Neural Architectures from Fundamental Operations. - Julia Costacurta, Shaunak Bhandarkar, David M. Zoltowski, Scott W. Linderman:
Structured flexibility in recurrent neural networks via neuromodulation. - Felipe Garrido-Lucero, Benjamin Heymann, Maxime Vono, Patrick Loiseau, Vianney Perchet:
DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation. - Xingyu Zhu, Beier Zhu, Yi Tan, Shuo Wang, Yanbin Hao, Hanwang Zhang:
Enhancing Zero-Shot Vision Models by Label-Free Prompt Distribution Learning and Bias Correcting. - Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Yifan Chen, Han Zhao, Qingfu Zhang:
LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch. - Shaurya Dewan, Rushikesh Zawar, Prakanshul Saxena, Yingshan Chang, Andrew F. Luo, Yonatan Bisk:
Diffusion PID: Interpreting Diffusion via Partial Information Decomposition. - Bing Cao, Yinan Xia, Yi Ding, Changqing Zhang, Qinghua Hu:
Test-Time Dynamic Image Fusion. - Huilong Jin, Yingxue Zhang, Lei Shi, Shuang Zhang, Feifei Kou, Jiapeng Yang, Chuangying Zhu, Jia Luo:
An End-To-End Graph Attention Network Hashing for Cross-Modal Retrieval. - Haoye Dong, Aviral Chharia, Wenbo Gou, Francisco Vicente Carrasco, Fernando De la Torre:
Hamba: Single-view 3D Hand Reconstruction with Graph-guided Bi-Scanning Mamba. - Zhengyi Luo, Jinkun Cao, Sammy Christen, Alexander Winkler, Kris Kitani, Weipeng Xu:
Omnigrasp: Grasping Diverse Objects with Simulated Humanoids. - Zifan Song, Yudong Wang, Wenwei Zhang, Kuikun Liu, Chengqi Lyu, Demin Song, Qipeng Guo, Hang Yan, Dahua Lin, Kai Chen, Cairong Zhao:
AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source Data. - Xiaoyuan Zhang, Genghui Li, Xi Lin, Yichi Zhang, Yifan Chen, Qingfu Zhang:
Gliding over the Pareto Front with Uniform Designs. - Manuel Meier, Berken Utku Demirel, Christian Holz:
WildPPG: A Real-World PPG Dataset of Long Continuous Recordings. - Wanhua Li, Zibin Meng, Jiawei Zhou, Donglai Wei, Chuang Gan, Hanspeter Pfister:
SocialGPT: Prompting LLMs for Social Relation Reasoning via Greedy Segment Optimization. - Recep Yusuf Bekci:
Online Learning of Delayed Choices. - Jeremias Traub, Till J. Bungert, Carsten T. Lüth, Michael Baumgartner, Klaus H. Maier-Hein, Lena Maier-Hein, Paul F. Jaeger:
Overcoming Common Flaws in the Evaluation of Selective Classification Systems. - Shentong Mo, Peter Tong:
Connecting Joint-Embedding Predictive Architecture with Contrastive Self-supervised Learning. - Anqi Mao, Mehryar Mohri, Yutao Zhong:
Multi-Label Learning with Stronger Consistency Guarantees. - Xinyi Xu, Shuaiqi Wang, Chuan Sheng Foo, Bryan Kian Hsiang Low, Giulia Fanti:
Data Distribution Valuation. - Zander W. Blasingame, Chen Liu:
AdjointDEIS: Efficient Gradients for Diffusion Models. - Connor Brennan, Andrew Williams, Omar G. Younis, Vedant Vyas, Daria Yasafova, Irina Rish:
Using Unity to Help Solve Reinforcement Learning. - Or Sheffet, Daniel Omer:
Differentially Private Equivalence Testing for Continuous Distributions and Applications. - Haozhe Tian, Homayoun Hamedmoghadam, Robert Shorten, Pietro Ferraro:
Reinforcement Learning with Adaptive Regularization for Safe Control of Critical Systems. - David Samuel:
BERTs are Generative In-Context Learners. - Jiahe Bai, Baojian Zhou, Deqing Yang, Yanghua Xiao:
Faster Local Solvers for Graph Diffusion Equations. - Dailing Zhang, Shiyu Hu, Xiaokun Feng, Xuchen Li, Meiqi Wu, Jing Zhang, Kaiqi Huang:
Beyond Accuracy: Tracking more like Human via Visual Search. - Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju:
Credit Attribution and Stable Compression. - Junyang Wang, Haiyang Xu, Haitao Jia, Xi Zhang, Ming Yan, Weizhou Shen, Ji Zhang, Fei Huang, Jitao Sang:
Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration. - Mohammad Mahmudul Alam, Alexander Oberle, Edward Raff, Stella Biderman, Tim Oates, James Holt:
A Walsh Hadamard Derived Linear Vector Symbolic Architecture. - Wei Liu, Chenxi Wang, Yifei Wang, Zihao Xie, Rennai Qiu, Yufan Dang, Zhuoyun Du, Weize Chen, Cheng Yang, Chen Qian:
Autonomous Agents for Collaborative Task under Information Asymmetry. - Jingwei Liu, Ling Yang, Hongyan Li, Shenda Hong:
Retrieval-Augmented Diffusion Models for Time Series Forecasting. - Hadi Hosseini, Debmalya Mandal, Amrit Puhan:
The Surprising Effectiveness of SP Voting with Partial Preferences. - Qijian Zhang, Junhui Hou, Wenping Wang, Ying He:
Flatten Anything: Unsupervised Neural Surface Parameterization. - Lin Gui, Cristina Garbacea, Victor Veitch:
BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling. - Hyunseok Lee, Jihoon Tack, Jinwoo Shin:
ReMoDetect: Reward Models Recognize Aligned LLM's Generations. - Atli Kosson, Bettina Messmer, Martin Jaggi:
Analyzing & Reducing the Need for Learning Rate Warmup in GPT Training. - Niki Maria Foteinopoulou, Enjie Ghorbel, Djamila Aouada:
A Hitchhiker's Guide to Fine-Grained Face Forgery Detection Using Common Sense Reasoning. - Siyuan Xu, Minghui Zhu:
Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator. - Ivan Butakov, Aleksander Tolmachev, Sofia Malanchuk, Anna Neopryatnaya, Alexey A. Frolov:
Mutual Information Estimation via Normalizing Flows. - Haozhe Zhao, Xiaojian (Shawn) Ma, Liang Chen, Shuzheng Si, Rujie Wu, Kaikai An, Peiyu Yu, Minjia Zhang, Qing Li, Baobao Chang:
UltraEdit: Instruction-based Fine-Grained Image Editing at Scale. - Jason Yang, Ariane Mora, Shengchao Liu, Bruce J. Wittmann, Animashree Anandkumar, Frances H. Arnold, Yisong Yue:
CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes. - Yiwei Zhou, Xiaobo Xia, Zhiwei Lin, Bo Han, Tongliang Liu:
Few-Shot Adversarial Prompt Learning on Vision-Language Models. - Fangjinhua Wang, Marie-Julie Rakotosaona, Michael Niemeyer, Richard Szeliski, Marc Pollefeys, Federico Tombari:
UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections. - Huzi Cheng, Joshua W. Brown:
Goal Reduction with Loop-Removal Accelerates RL and Models Human Brain Activity in Goal-Directed Learning. - Adrian Bulat, Yassine Ouali, Georgios Tzimiropoulos:
QBB: Quantization with Binary Bases for LLMs. - Xiang Li, Jian Ding, Mohamed Elhoseiny:
VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understanding. - Naoki Hiratani:
Disentangling and mitigating the impact of task similarity for continual learning. - Asaf Cassel, Aviv Rosenberg:
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes. - Tianyi Zhang, Jonah Yi, Zhaozhuo Xu, Anshumali Shrivastava:
KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization. - Qiannan Zhang, Weishen Pan, Zilong Bai, Chang Su, Fei Wang:
Unified Insights: Harnessing Multi-modal Data for Phenotype Imputation via View Decoupling. - Lasse Vuursteen:
Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime. - Chengzhengxu Li, Xiaoming Liu, Zhaohan Zhang, Yichen Wang, Chen Liu, Yu Lan, Chao Shen:
Concentrate Attention: Towards Domain-Generalizable Prompt Optimization for Language Models. - Chao Chen, Chenghua Guo, Rufeng Chen, Guixiang Ma, Ming Zeng, Xiangwen Liao, Xi Zhang, Sihong Xie:
Training for Stable Explanation for Free. - Bernardo Esteves, Miguel Vasco, Francisco S. Melo:
NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks. - Ruohan Li, Yiqun Xie, Xiaowei Jia, Dongdong Wang, Yanhua Li, Yingxue Zhang, Zhihao Wang, Zhili Li:
SolarCube: An Integrative Benchmark Dataset Harnessing Satellite and In-situ Observations for Large-scale Solar Energy Forecasting. - Junyu Liu, Xiangjun Peng:
Feint Behaviors and Strategies: Formalization, Implementation and Evaluation. - Yixiao Xu, Binxing Fang, Mohan Li, Keke Tang, Zhihong Tian:
LT-Defense: Searching-free Backdoor Defense via Exploiting the Long-tailed Effect. - Yang Yang, Wendi Ren, Shuang Li:
HyperLogic: Enhancing Diversity and Accuracy in Rule Learning with HyperNets. - Zhongzhen Huang, Yankai Jiang, Rongzhao Zhang, Shaoting Zhang, Xiaofan Zhang:
CAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor Segmentation. - Jamie Lohoff, Emre Neftci:
Optimizing Automatic Differentiation with Deep Reinforcement Learning. - Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof:
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. - Eric Balkanski, Will Ma, Andreas Maggiori:
Fair Secretaries with Unfair Predictions. - Alexander Tyurin, Marta Pozzi, Ivan Ilin, Peter Richtárik:
Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity. - Lucas Slot, Stefan Tiegel, Manuel Wiedmer:
Testably Learning Polynomial Threshold Functions. - Lakshmi Narasimhan Govindarajan, Abhiram Iyer, Valmiki Kothare, Ila Fiete:
Flexible Context-Driven Sensory Processing in Dynamical Vision Models. - Andres Potapczynski, Shikai Qiu, Marc Finzi, Christopher Ferri, Charlie Chen, Micah Goldblum, C. Bayan Bruss, Christopher De Sa, Andrew Gordon Wilson:
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices. - Jiamian Wang, Pichao Wang, Dongfang Liu, Qiang Guan, Sohail A. Dianat, Majid Rabbani, Raghuveer Rao, Zhiqiang Tao:
Diffusion-Inspired Truncated Sampler for Text-Video Retrieval. - Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley, Otmar Hilliges, Romann M. Weber:
LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models. - Huayang Huang, Yu Wu, Qian Wang:
ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimization. - Nikhil Behari, Edwin Zhang, Yunfan Zhao, Aparna Taneja, Dheeraj Nagaraj, Milind Tambe:
A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health. - Jitao Zhao, Di Jin, Meng Ge, Lianze Shan, Xin Wang, Dongxiao He, Zhiyong Feng:
FUG: Feature-Universal Graph Contrastive Pre-training for Graphs with Diverse Node Features. - Yiqun Mei, Jiacong Xu, Vishal M. Patel:
ReGS: Reference-based Controllable Scene Stylization with Gaussian Splatting. - Atharva Mete, Haotian Xue, Albert Wilcox, Yongxin Chen, Animesh Garg:
QueST: Self-Supervised Skill Abstractions for Learning Continuous Control. - Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu:
DiffPhyCon: A Generative Approach to Control Complex Physical Systems. - Wenliang Zhao, Minglei Shi, Xumin Yu, Jie Zhou, Jiwen Lu:
FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner. - Zhengbang Zhu, Minghuan Liu, Liyuan Mao, Bingyi Kang, Minkai Xu, Yong Yu, Stefano Ermon, Weinan Zhang:
MADiff: Offline Multi-agent Learning with Diffusion Models. - Gabriele Farina, Charilaos Pipis:
Polynomial-Time Computation of Exact $\Phi$-Equilibria in Polyhedral Games. - Sheng-Yu Wang, Aaron Hertzmann, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang:
Data Attribution for Text-to-Image Models by Unlearning Synthesized Images. - Xi Yu, Shinjae Yoo, Yuewei Lin:
CLIPCEIL: Domain Generalization through CLIP via Channel rEfinement and Image-text aLignment. - Linus Jeary, Tom Kuipers, Mehran Hosseini, Nicola Paoletti:
Verifiably Robust Conformal Prediction. - Zhuopeng Xu, Yujie Li, Cheng Liu, Ning Gui:
Ordering-Based Causal Discovery for Linear and Nonlinear Relations. - Longfei Ma, Yiyou Sun, Kaize Ding, Zemin Liu, Fei Wu:
Revisiting Score Propagation in Graph Out-of-Distribution Detection. - Ian Covert, Chanwoo Kim, Su-In Lee, James Y. Zou, Tatsunori B. Hashimoto:
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution. - Haocheng Luo, Tuan Truong, Tung Pham, Mehrtash Harandi, Dinh Q. Phung, Trung Le:
Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization. - Ruikai Cui, Xibin Song, Weixuan Sun, Senbo Wang, Weizhe Liu, Shenzhou Chen, Taizhang Shang, Yang Li, Nick Barnes, Hongdong Li, Pan Ji:
LAM3D: Large Image-Point Clouds Alignment Model for 3D Reconstruction from Single Image. - Seijin Kobayashi, Yassir Akram, Johannes von Oswald:
Weight decay induces low-rank attention layers. - Lingxiang Jia, Yuchen Ying, Zunlei Feng, Zipeng Zhong, Shaolun Yao, Jiacong Hu, Mingjiang Duan, Xingen Wang, Jie Song, Mingli Song:
Association Pattern-aware Fusion for Biological Entity Relationship Prediction. - Yongliang Shen, Kaitao Song, Xu Tan, Wenqi Zhang, Kan Ren, Siyu Yuan, Weiming Lu, Dongsheng Li, Yueting Zhuang:
TaskBench: Benchmarking Large Language Models for Task Automation. - Hang Zhou, Yehui Tang, Haochen Qin, Yujie Yang, Renren Jin, Deyi Xiong, Kai Han, Yunhe Wang:
Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning. - Boyao Li, Alexander Thomson, Houssam Nassif, Matthew Engelhard, David Page:
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. - Benedikt Böck, Sadaf Syed, Wolfgang Utschick:
Sparse Bayesian Generative Modeling for Compressive Sensing. - Hezhe Qiao, Qingsong Wen, Xiaoli Li, Ee-Peng Lim, Guansong Pang:
Generative Semi-supervised Graph Anomaly Detection. - Xiuying Wei, Skander Moalla, Razvan Pascanu, Caglar Gulcehre:
Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers. - Shihong Ding, Long Yang, Luo Luo, Cong Fang:
Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition. - Rayna Andreeva, Benjamin Dupuis, Rik Sarkar, Tolga Birdal, Umut Simsekli:
Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms. - Zhanhui Zhou, Zhixuan Liu, Jie Liu, Zhichen Dong, Chao Yang, Yu Qiao:
Weak-to-Strong Search: Align Large Language Models via Searching over Small Language Models. - Binghui Xie, Yixuan Wang, Yongqiang Chen, Kaiwen Zhou, Yu Li, Wei Meng, James Cheng:
HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection. - Shivam Grover, Amin Jalali, Ali Etemad:
Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations. - Youcheng Zhang, Liwen Zhang, ZijunHu, Pengcheng Pi, Teng Li, Yuanpei Chen, Shi Peng, Zhe Ma:
TARSS-Net: Temporal-Aware Radar Semantic Segmentation Network. - Jun-Kun Chen, Yu-Xiong Wang:
ProEdit: Simple Progression is All You Need for High-Quality 3D Scene Editing. - Laurent Mertens, Elahe Yargholi, Hans P. Op de Beeck, Jan Van den Stock, Joost Vennekens:
FindingEmo: An Image Dataset for Emotion Recognition in the Wild. - Dan Shi, Renren Jin, Tianhao Shen, Weilong Dong, Xinwei Wu, Deyi Xiong:
IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons. - Zhuoyan Li, Ming Yin:
Utilizing Human Behavior Modeling to Manipulate Explanations in AI-Assisted Decision Making: The Good, the Bad, and the Scary. - Yu Zeng, Yang Zhang, Jiachen Liu, Linlin Shen, Kaijun Deng, Weizhao He, Jinbao Wang:
HairDiffusion: Vivid Multi-Colored Hair Editing via Latent Diffusion. - Vladimir Malinovskii, Denis Mazur, Ivan Ilin, Denis Kuznedelev, Konstantin Burlachenko, Kai Yi, Dan Alistarh, Peter Richtárik:
PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression. - Klara Kaleb, Barbara Feulner, Juan Gallego, Claudia Clopath:
Feedback control guides credit assignment in recurrent neural networks. - Abhinav Joshi, Areeb Ahmad, Ashutosh Modi:
COLD: Causal reasOning in cLosed Daily activities. - Jianyi Zhang, Da-Cheng Juan, Cyrus Rashtchian, Chun-Sung Ferng, Heinrich Jiang, Yiran Chen:
SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models. - Jiongxiao Wang, Jiazhao Li, Yiquan Li, Xiangyu Qi, Junjie Hu, Sharon Li, Patrick McDaniel, Muhao Chen, Bo Li, Chaowei Xiao:
BackdoorAlign: Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment. - Peiyuan Feng, Yichen He, Guanhua Huang, Yuan Lin, Hanchong Zhang, Yuchen Zhang, Hang Li:
AGILE: A Novel Reinforcement Learning Framework of LLM Agents. - Hang Yin, Xiuwei Xu, Zhenyu Wu, Jie Zhou, Jiwen Lu:
SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation. - Reuben Adams, John Shawe-Taylor, Benjamin Guedj:
Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound. - Xixi Wu, Yifei Shen, Caihua Shan, Kaitao Song, Siwei Wang, Bohang Zhang, Jiarui Feng, Hong Cheng, Wei Chen, Yun Xiong, Dongsheng Li:
Can Graph Learning Improve Planning in LLM-based Agents? - Junoh Lee, Changyeon Won, Hyunjun Jung, Inhwan Bae, Hae-Gon Jeon:
Fully Explicit Dynamic Gaussian Splatting. - Timon Barlag, Vivian Holzapfel, Laura Strieker, Jonni Virtema, Heribert Vollmer:
Graph Neural Networks and Arithmetic Circuits. - Nikil Roashan Selvam, Amil Merchant, Stefano Ermon:
Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations. - Alexander David Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob N. Foerster:
Can Learned Optimization Make Reinforcement Learning Less Difficult? - Jiatao Gu, Ying Shen, Shuangfei Zhai, Yizhe Zhang, Navdeep Jaitly, Joshua M. Susskind:
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling. - Qingqi Zhang, Ruize Xu, Risi Kondor:
Schur Nets: exploiting local structure for equivariance in higher order graph neural networks. - Runjia Zeng, Cheng Han, Qifan Wang, Chunshu Wu, Tong Geng, Lifu Huang, Ying Nian Wu, Dongfang Liu:
Visual Fourier Prompt Tuning. - Benjamin Rozonoyer, Michael Boratko, Dhruvesh Patel, Wenlong Zhao, Shib Sankar Dasgupta, Hung Le, Andrew McCallum:
Learning Representations for Hierarchies with Minimal Support. - Chester Holtz, Pengwen Chen, Zhengchao Wan, Chung-Kuan Cheng, Gal Mishne:
Continuous Partitioning for Graph-Based Semi-Supervised Learning. - Hezhen Hu, Zhiwen Fan, Tianhao Wu, Yihan Xi, Seoyoung Lee, Georgios Pavlakos, Zhangyang Wang:
Expressive Gaussian Human Avatars from Monocular RGB Video. - Bobak T. Kiani, Jason Wang, Melanie Weber:
Hardness of Learning Neural Networks under the Manifold Hypothesis. - Wei Li, Hehe Fan, Yongkang Wong, Mohan S. Kankanhalli, Yi Yang:
TOPA: Extending Large Language Models for Video Understanding via Text-Only Pre-Alignment. - Yibo Wang, Jun-Yi Hang, Min-Ling Zhang:
Multi-Label Open Set Recognition. - Keying Kuang, Frances Dean, Jack B. Jedlicki, David Ouyang, Anthony Philippakis, David A. Sontag, Ahmed M. Alaa:
Med-Real2Sim: Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning. - Feng Lu, Xinyao Zhang, Canming Ye, Shuting Dong, Lijun Zhang, Xiangyuan Lan, Chun Yuan:
SuperVLAD: Compact and Robust Image Descriptors for Visual Place Recognition. - Xavier Gonzalez, Andrew Warrington, Jimmy T. H. Smith, Scott W. Linderman:
Towards Scalable and Stable Parallelization of Nonlinear RNNs. - Zhifan Ye, Chenxi Wan, Chaojian Li, Jihoon Hong, Sixu Li, Leshu Li, Yongan Zhang, Yingyan (Celine) Lin:
3D Gaussian Rendering Can Be Sparser: Efficient Rendering via Learned Fragment Pruning. - Alexander Soen, Ke Sun:
Trade-Offs of Diagonal Fisher Information Matrix Estimators. - Yue Liu, Shihao Zhu, Jun Xia, Yingwei Ma, Jian Ma, Xinwang Liu, Shengju Yu, Kejun Zhang, Wenliang Zhong:
End-to-end Learnable Clustering for Intent Learning in Recommendation. - Duo Wang, Yuan Zuo, Fengzhi Li, Junjie Wu:
LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings. - Yooju Shin, Jaehyun Park, Susik Yoon, Hwanjun Song, Byung Suk Lee, Jae-Gil Lee:
Exploiting Representation Curvature for Boundary Detection in Time Series. - Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier de Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin:
WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks. - Qinggang Zhang, Junnan Dong, Hao Chen, Daochen Zha, Zailiang Yu, Xiao Huang:
KnowGPT: Knowledge Graph based Prompting for Large Language Models. - Zhi Zheng, Changliang Zhou, Xialiang Tong, Mingxuan Yuan, Zhenkun Wang:
UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems. - Chong Ma, Hanqi Jiang, Wenting Chen, Yiwei Li, Zihao Wu, Xiaowei Yu, Zhengliang Liu, Lei Guo, Dajiang Zhu, Tuo Zhang, Dinggang Shen, Tianming Liu, Xiang Li:
Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning. - Desik Rengarajan, Nitin Ragothaman, Dileep Kalathil, Srinivas Shakkottai:
Federated Ensemble-Directed Offline Reinforcement Learning. - Ji-An Li, Corey Yishan Zhou, Marcus K. Benna, Marcelo G. Mattar:
Linking In-context Learning in Transformers to Human Episodic Memory. - Wuyang Chen, Jialin Song, Pu Ren, Shashank Subramanian, Dmitriy Morozov, Michael W. Mahoney:
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning. - Fei Shen, Jinhui Tang:
IMAGPose: A Unified Conditional Framework for Pose-Guided Person Generation. - Albert Gong, Kyuseong Choi, Raaz Dwivedi:
Supervised Kernel Thinning. - Xinyu Yuan, Zhihao Zhan, Zuobai Zhang, Manqi Zhou, Jianan Zhao, Boyu Han, Yue Li, Jian Tang:
Cell ontology guided transcriptome foundation model. - Mixue Xie, Shuang Li, Binhui Xie, Chi Harold Liu, Jian Liang, Zixun Sun, Ke Feng, Chengwei Zhu:
Weight Diffusion for Future: Learn to Generalize in Non-Stationary Environments. - Viet Ho Tam Thuc Do, Parham Eftekhar, Seyed Alireza Hosseini, Gene Cheung, Philip A. Chou:
Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors. - Mayank Shrivastava, Berivan Isik, Qiaobo Li, Sanmi Koyejo, Arindam Banerjee:
Sketching for Distributed Deep Learning: A Sharper Analysis. - Yonghan Jung, Jin Tian, Elias Bareinboim:
Unified Covariate Adjustment for Causal Inference. - Elizabeth Collins-Woodfin, Inbar Seroussi, Begoña García Malaxechebarría, Andrew W. Mackenzie, Elliot Paquette, Courtney Paquette:
The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms. - Biqing Qi, Yiang Luo, Junqi Gao, Pengfei Li, Kai Tian, Zhiyuan Ma, Bowen Zhou:
Exploring Adversarial Robustness of Deep State Space Models. - Joseph Ortiz, Antoine Dedieu, Wolfgang Lehrach, J. Swaroop Guntupalli, Carter Wendelken, Ahmad Humayun, Sivaramakrishnan Swaminathan, Guangyao Zhou, Miguel Lázaro-Gredilla, Kevin P. Murphy:
DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors. - Haoyu Dong, Huiqiao Fu, Wentao Xu, Zhehao Zhou, Chunlin Chen:
EASI: Evolutionary Adversarial Simulator Identification for Sim-to-Real Transfer. - Yang Zhou, Tan Li Hui Faith, Yanyu Xu, Sicong Leng, Xinxing Xu, Yong Liu, Rick Siow Mong Goh:
BenchX: A Unified Benchmark Framework for Medical Vision-Language Pretraining on Chest X-Rays. - Awni Altabaa, Zhuoran Yang:
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games. - Ziqiao Wang, Yongyi Mao:
On $f$-Divergence Principled Domain Adaptation: An Improved Framework. - Woo Kyung Kim, Youngseok Lee, Jooyoung Kim, Honguk Woo:
LLM-based Skill Diffusion for Zero-shot Policy Adaptation. - Zhen Chen, Yi Zhang, Fu Wang, Xingyu Zhao, Xiaowei Huang, Wenjie Ruan:
TARP-VP: Towards Evaluation of Transferred Adversarial Robustness and Privacy on Label Mapping Visual Prompting Models. - Antonio Terpin, Nicolas Lanzetti, Martín Gadea, Florian Dörfler:
Learning diffusion at lightspeed. - Zechen Bai, Tong He, Haiyang Mei, Pichao Wang, Ziteng Gao, Joya Chen, Lei Liu, Zheng Zhang, Mike Zheng Shou:
One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos. - Wei Yu, Bowen Yang, Qinglin Liu, Jianing Li, Shengping Zhang, Xiangyang Ji:
Rethinking Imbalance in Image Super-Resolution for Efficient Inference. - Boqiang Zhang, Zuan Gao, Yadong Qu, Hongtao Xie:
How Control Information Influences Multilingual Text Image Generation and Editing? - Jesus Zarzar, Bernard Ghanem:
SplitNeRF: Split Sum Approximation Neural Field for Joint Geometry, Illumination, and Material Estimation. - Kai Sandbrink, Jan P. Bauer, Alexandra Maria Proca, Andrew M. Saxe, Christopher Summerfield, Ali Hummos:
Flexible task abstractions emerge in linear networks with fast and bounded units. - Deepak Sridhar, Abhishek Peri, Rohith Rachala, Nuno Vasconcelos:
Adapting Diffusion Models for Improved Prompt Compliance and Controllable Image Synthesis. - Weihao Lu, Haobo Zhang, Yicheng Li, Qian Lin:
On the Saturation Effects of Spectral Algorithms in Large Dimensions. - Tianjing Zhang, Yuhui Quan, Hui Ji:
Cross-Scale Self-Supervised Blind Image Deblurring via Implicit Neural Representation. - Yuanning Cui, Zequn Sun, Wei Hu:
A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning. - Ali Younis, Erik B. Sudderth:
Learning to be Smooth: An End-to-End Differentiable Particle Smoother. - Lingxiao Zhao, Xueying Ding, Leman Akoglu:
Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation. - Weichao Zhao, Hao Feng, Qi Liu, Jingqun Tang, Binghong Wu, Lei Liao, Shu Wei, Yongjie Ye, Hao Liu, Wengang Zhou, Houqiang Li, Can Huang:
TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy. - Chujie Gao, Siyuan Wu, Yue Huang, Dongping Chen, Qihui Zhang, Zhengyan Fu, Yao Wan, Lichao Sun, Xiangliang Zhang:
HonestLLM: Toward an Honest and Helpful Large Language Model. - Tianle Gu, Zeyang Zhou, Kexin Huang, Dandan Liang, Yixu Wang, Haiquan Zhao, Yuanqi Yao, Xingge Qiao, Keqing Wang, Yujiu Yang, Yan Teng, Yu Qiao, Yingchun Wang:
MLLMGuard: A Multi-dimensional Safety Evaluation Suite for Multimodal Large Language Models. - Yiheng Wang, Tianyu Wang, YuYing Zhang, Hongji Zhang, Haoyu Zheng, Guanjie Zheng, Linghe Kong:
UrbanDataLayer: A Unified Data Pipeline for Urban Science. - Thomas W. Mitchel, Michael J. Taylor, Vincent Sitzmann:
Neural Isometries: Taming Transformations for Equivariant ML. - Yutao Sun, Li Dong, Yi Zhu, Shaohan Huang, Wenhui Wang, Shuming Ma, Quanlu Zhang, Jianyong Wang, Furu Wei:
You Only Cache Once: Decoder-Decoder Architectures for Language Models. - Xingyu Zhou, Komo (Wei) Zhang:
Locally Private and Robust Multi-Armed Bandits. - Samyadeep Basu, Martin Grayson, Cecily Morrison, Besmira Nushi, Soheil Feizi, Daniela Massiceti:
Understanding Information Storage and Transfer in Multi-Modal Large Language Models. - Bin Ren, Yawei Li, Jingyun Liang, Rakesh Ranjan, Mengyuan Liu, Rita Cucchiara, Luc Van Gool, Ming-Hsuan Yang, Nicu Sebe:
Sharing Key Semantics in Transformer Makes Efficient Image Restoration. - Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang:
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. - Zhe Zhao, Haibin Wen, Zikang Wang, Pengkun Wang, Fanfu Wang, Song Lai, Qingfu Zhang, Yang Wang:
Breaking Long-Tailed Learning Bottlenecks: A Controllable Paradigm with Hypernetwork-Generated Diverse Experts. - Haipeng Luo, Spandan Senapati, Vatsal Sharan:
Optimal Multiclass U-Calibration Error and Beyond. - Mohammad Sadil Khan, Sankalp Sinha, Talha Uddin Sheikh, Didier Stricker, Sk Aziz Ali, Muhammad Zeshan Afzal:
Text2CAD: Generating Sequential CAD Designs from Beginner-to-Expert Level Text Prompts. - Xuanyu Yi, Zike Wu, Qiuhong Shen, Qingshan Xu, Pan Zhou, Joo-Hwee Lim, Shuicheng Yan, Xinchao Wang, Hanwang Zhang:
MVGamba: Unify 3D Content Generation as State Space Sequence Modeling. - Ang Bian, Wei Li, Hangjie Yuan, Chengrong Yu, Mang Wang, Zixiang Zhao, Aojun Lu, Pengliang Ji, Tao Feng:
Make Continual Learning Stronger via C-Flat. - Jonathan Thomm, Giacomo Camposampiero, Aleksandar Terzic, Michael Hersche, Bernhard Schölkopf, Abbas Rahimi:
Limits of Transformer Language Models on Learning to Compose Algorithms. - Xiaoge Deng, Tao Sun, Shengwei Li, Dongsheng Li, Xicheng Lu:
Stability and Generalization of Asynchronous SGD: Sharper Bounds Beyond Lipschitz and Smoothness. - Yubo Ye, Maryam Toloubidokhti, Sumeet Vadhavkar, Xiajun Jiang, Huafeng Liu, Linwei Wang:
On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution. - Gongfan Fang, Hongxu Yin, Saurav Muralidharan, Greg Heinrich, Jeff Pool, Jan Kautz, Pavlo Molchanov, Xinchao Wang:
MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models. - Divyansh Pareek, Simon S. Du, Sewoong Oh:
Understanding the Gains from Repeated Self-Distillation. - Dongfang Li, Zhenyu Liu, Xinshuo Hu, Zetian Sun, Baotian Hu, Min Zhang:
In-Context Learning State Vector with Inner and Momentum Optimization. - Yuxuan Tong, Xiwen Zhang, Rui Wang, Ruidong Wu, Junxian He:
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving. - Ori Press, Andreas Hochlehnert, Ameya Prabhu, Vishaal Udandarao, Ofir Press, Matthias Bethge:
CiteME: Can Language Models Accurately Cite Scientific Claims? - Yue Lu, Shizhou Zhang, De Cheng, Yinghui Xing, Nannan Wang, Peng Wang, Yanning Zhang:
Visual Prompt Tuning in Null Space for Continual Learning. - Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna:
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better. - Polina Turishcheva, Max F. Burg, Fabian H. Sinz, Alexander S. Ecker:
Reproducibility of predictive networks for mouse visual cortex. - Rohan Baskar Prabhakar, Hengrui Zhang, David Wentzlaff:
Kraken: Inherently Parallel Transformers For Efficient Multi-Device Inference. - Hongyu Shen, Yici Yan, Zhizhen Jane Zhao:
DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection. - Cuong Dao, Phi Le Nguyen, Truong Thao Nguyen, Nghia Hoang:
Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques. - Hui Wei, Zhixiang Wang, Kewei Zhang, Jiaqi Hou, Yuanwei Liu, Hao Tang, Zheng Wang:
Revisiting Adversarial Patches for Designing Camera-Agnostic Attacks against Person Detection. - Gang Liu, Jiaxin Xu, Tengfei Luo, Meng Jiang:
Graph Diffusion Transformers for Multi-Conditional Molecular Generation. - Seungju Han, Kavel Rao, Allyson Ettinger, Liwei Jiang, Bill Yuchen Lin, Nathan Lambert, Yejin Choi, Nouha Dziri:
WildGuard: Open One-stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs. - Hrittik Roy, Marco Miani, Carl Henrik Ek, Philipp Hennig, Marvin Pförtner, Lukas Tatzel, Søren Hauberg:
Reparameterization invariance in approximate Bayesian inference. - Matteo Zecchin, Osvaldo Simeone:
Localized Adaptive Risk Control. - Arjun Subramonian, Jian Kang, Yizhou Sun:
Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks. - Michael Crawshaw, Mingrui Liu:
Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis. - Julius Hense, Mina Jamshidi Idaji, Oliver Eberle, Thomas Schnake, Jonas Dippel, Laure Ciernik, Oliver Buchstab, Andreas Mock, Frederick Klauschen, Klaus-Robert Müller:
xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology. - Ayush Sawarni, Nirjhar Das, Siddharth Barman, Gaurav Sinha:
Generalized Linear Bandits with Limited Adaptivity. - Gefen Dawidowicz, Elad Hirsch, Ayellet Tal:
Image-aware Evaluation of Generated Medical Reports. - Jiapu Wang, Kai Sun, Linhao Luo, Wei Wei, Yongli Hu, Alan Wee-Chung Liew, Shirui Pan, Baocai Yin:
Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning. - Joowon Lee, Jared D. Huling, Guanhua Chen:
An effective framework for estimating individualized treatment rules. - Taira Tsuchiya, Shinji Ito:
A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $\Theta(T^{2/3})$ and its Application to Best-of-Both-Worlds. - Runze Yang, Longbing Cao, Jie Yang, Jianxun Li:
Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting. - Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco:
Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints. - Guhao Feng, Han Zhong:
Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity. - Hao Shao, Shengju Qian, Han Xiao, Guanglu Song, Zhuofan Zong, Letian Wang, Yu Liu, Hongsheng Li:
Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning. - Xuandong Zhao, Kexun Zhang, Zihao Su, Saastha Vasan, Ilya Grishchenko, Christopher Kruegel, Giovanni Vigna, Yu-Xiang Wang, Lei Li:
Invisible Image Watermarks Are Provably Removable Using Generative AI. - Qiang Li, Hoi-To Wai:
Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss. - Ziyu Liu, Tao Chu, Yuhang Zang, Xilin Wei, Xiaoyi Dong, Pan Zhang, Zijian Liang, Yuanjun Xiong, Yu Qiao, Dahua Lin, Jiaqi Wang:
MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs. - Jinda Jia, Cong Xie, Hanlin Lu, Daoce Wang, Hao Feng, Chengming Zhang, Baixi Sun, Haibin Lin, Zhi Zhang, Xin Liu, Dingwen Tao:
SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training. - Mingxuan Ju, William Shiao, Zhichun Guo, Yanfang Ye, Yozen Liu, Neil Shah, Tong Zhao:
How Does Message Passing Improve Collaborative Filtering? - Jung-Hun Kim, Milan Vojnovic, Se-Young Yun:
An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints. - Aniket Das, Dheeraj Nagaraj, Soumyabrata Pal, Arun Sai Suggala, Prateek Varshney:
Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD. - Alexander Nikitin, Jannik Kossen, Yarin Gal, Pekka Marttinen:
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities. - Ruochen Liu, Hao Chen, Yuanchen Bei, Qijie Shen, Fangwei Zhong, Senzhang Wang, Jianxin Wang:
Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination. - Jonathan Hayase, Alisa Liu, Yejin Choi, Sewoong Oh, Noah A. Smith:
Data Mixture Inference Attack: BPE Tokenizers Reveal Training Data Compositions. - Jörg K. H. Franke, Michael Hefenbrock, Gregor Köhler, Frank Hutter:
Improving Deep Learning Optimization through Constrained Parameter Regularization. - Luke Eilers, Raoul-Martin Memmesheimer, Sven Goedeke:
A generalized neural tangent kernel for surrogate gradient learning. - Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann:
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space. - Haiquan Lu, Yefan Zhou, Shiwei Liu, Zhangyang Wang, Michael W. Mahoney, Yaoqing Yang:
AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models. - Heeseong Shin, Chaehyun Kim, Sunghwan Hong, Seokju Cho, Anurag Arnab, Paul Hongsuck Seo, Seungryong Kim:
Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels. - Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu:
Sample Efficient Bayesian Learning of Causal Graphs from Interventions. - Shangkun Sun, Jiaming Liu, Huaxia Li, Guoqing Liu, Thomas H. Li, Wei Gao:
StreamFlow: Streamlined Multi-Frame Optical Flow Estimation for Video Sequences. - Sanae Lotfi, Yilun Kuang, Marc Finzi, Brandon Amos, Micah Goldblum, Andrew Gordon Wilson:
Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models. - Han Huang, Haitian Zhong, Tao Yu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark. - Yue Wang, Zhongchang Sun, Shaofeng Zou:
A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch. - Alex Elenter, Spyros Angelopoulos, Christoph Dürr, Yanni Lefki:
Overcoming Brittleness in Pareto-Optimal Learning Augmented Algorithms. - Shirley Wu, Kaidi Cao, Bruno Ribeiro, James Y. Zou, Jure Leskovec:
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts. - Yuhang Wen, Mengyuan Liu, Songtao Wu, Beichen Ding:
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition. - Joel Daniel Andersson, Monika Henzinger, Rasmus Pagh, Teresa Anna Steiner, Jalaj Upadhyay:
Continual Counting with Gradual Privacy Expiration. - Ke Liang, Yue Liu, Hao Li, Lingyuan Meng, Suyuan Liu, Siwei Wang, Sihang Zhou, Xinwang Liu:
Clustering then Propagation: Select Better Anchors for Knowledge Graph Embedding. - Fangcong Yin, Xi Ye, Greg Durrett:
LoFiT: Localized Fine-tuning on LLM Representations. - Jie Ma, Min Hu, Pinghui Wang, Wangchun Sun, Lingyun Song, Hongbin Pei, Jun Liu, Youtian Du:
Look, Listen, and Answer: Overcoming Biases for Audio-Visual Question Answering. - Yawar Siddiqui, Tom Monnier, Filippos Kokkinos, Mahendra Kariya, Yanir Kleiman, Emilien Garreau, Oran Gafni, Natalia Neverova, Andrea Vedaldi, Roman Shapovalov, David Novotný:
Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials. - Chunlin Tian, Zhan Shi, Zhijiang Guo, Li Li, Cheng-Zhong Xu:
HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning. - Yijing Liu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Wei Chen:
Graph Diffusion Policy Optimization. - Biao Gong, Shuai Tan, Yutong Feng, Xiaoying Xie, Yuyuan Li, Chaochao Chen, Kecheng Zheng, Yujun Shen, Deli Zhao:
UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training. - Haixiang Sun, Ye Shi:
Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective. - Derui Zhu, Dingfan Chen, Xiongfei Wu, Jiahui Geng, Zhuo Li, Jens Grossklags, Lei Ma:
PrivAuditor: Benchmarking Data Protection Vulnerabilities in LLM Adaptation Techniques. - Puze Liu, Jonas Günster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Maric, Sylvain Calinon, Andrej Orsula, Miguel S. Olivares-Méndez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan R. Peters:
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. - Xiang Fu, Andrew S. Rosen, Kyle Bystrom, Rui Wang, Albert Musaelian, Boris Kozinsky, Tess E. Smidt, Tommi S. Jaakkola:
A Recipe for Charge Density Prediction. - Yongcheng Jing, Seok-Hee Hong, Dacheng Tao:
Deep Graph Mating. - Yingzhe Peng, Chenduo Hao, Xinting Hu, Jiawei Peng, Xin Geng, Xu Yang:
LIVE: Learnable In-Context Vector for Visual Question Answering. - Beomseok Kang, Priyabrata Saha, Sudarshan Sharma, Biswadeep Chakraborty, Saibal Mukhopadhyay:
Online Relational Inference for Evolving Multi-agent Interacting Systems. - Hefei Li, Chao Peng, Chenyang Xu, Zhengfeng Yang:
Open-Book Neural Algorithmic Reasoning. - Shahar Yadin, Noam Elata, Tomer Michaeli:
Classification Diffusion Models: Revitalizing Density Ratio Estimation. - Yearang Lee, Ho-Joong Kim, Seong-Whan Lee:
Text-Infused Attention and Foreground-Aware Modeling for Zero-Shot Temporal Action Detection. - Jianyi Yang, Pengfei Li, Adam Wierman, Shaolei Ren:
Online Budgeted Matching with General Bids. - Daniel de Vassimon Manela, Laura Battaglia, Robin J. Evans:
Marginal Causal Flows for Validation and Inference. - Liqiang Lin, Wenpeng Wu, Chi-Wing Fu, Hao Zhang, Hui Huang:
CRAYM: Neural Field Optimization via Camera RAY Matching. - Aaron Defazio, Xingyu Yang, Ahmed Khaled, Konstantin Mishchenko, Harsh Mehta, Ashok Cutkosky:
The Road Less Scheduled. - Mingyi Li, Xiao Zhang, Qi Wang, Tengfei Liu, Ruofan Wu, Weiqiang Wang, Fuzhen Zhuang, Hui Xiong, Dongxiao Yu:
Resource-Aware Federated Self-Supervised Learning with Global Class Representations. - Zhaokun Zhou, Yijie Lu, Yanhao Jia, Kaiwei Che, Jun Niu, Liwei Huang, Xinyu Shi, Yuesheng Zhu, Guoqi Li, Zhaofei Yu, Li Yuan:
Spiking Transformer with Experts Mixture. - Eric Zhao, Pranjal Awasthi, Zhengdao Chen, Sreenivas Gollapudi, Daniel Delling:
Semantic Routing via Autoregressive Modeling. - Peter A. Jansen, Marc-Alexandre Côté, Tushar Khot, Erin Bransom, Bhavana Dalvi Mishra, Bodhisattwa Prasad Majumder, Oyvind Tafjord, Peter Clark:
DiscoveryWorld: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents. - Zifan Liu, Amin Karbasi, Theodoros Rekatsinas:
TSDS: Data Selection for Task-Specific Model Finetuning. - Ashok Cutkosky, Zakaria Mhammedi:
Fully Unconstrained Online Learning. - Andy Yang, David Chiang, Dana Angluin:
Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages. - Sifei Liu, Shalini De Mello, Jan Kautz:
CosAE: Learnable Fourier Series for Image Restoration. - Hyun-Young Park, Shahab Asoodeh, Si-Hyeon Lee:
Exactly Minimax-Optimal Locally Differentially Private Sampling. - Zican Dong, Junyi Li, Xin Men, Xin Zhao, Bingning Wang, Zhen Tian, Weipeng Chen, Ji-Rong Wen:
Exploring Context Window of Large Language Models via Decomposed Positional Vectors. - Adarsh Jamadandi, Celia Rubio-Madrigal, Rebekka Burkholz:
Spectral Graph Pruning Against Over-Squashing and Over-Smoothing. - Shubham Chowdhary, Giulia De Pasquale, Nicolas Lanzetti, Ana-Andreea Stoica, Florian Dörfler:
Fairness in Social Influence Maximization via Optimal Transport. - Yuezhu Xu, S. Sivaranjani:
ECLipsE: Efficient Compositional Lipschitz Constant Estimation for Deep Neural Networks. - Mariia Vladimirova, Federico Pavone, Eustache Diemert:
FairJob: A Real-World Dataset for Fairness in Online Systems. - Xiao Yang, Kai Sun, Hao Xin, Yushi Sun, Nikita Bhalla, Xiangsen Chen, Sajal Choudhary, Rongze Daniel Gui, Ziran Will Jiang, Ziyu Jiang, Lingkun Kong, Brian Moran, Jiaqi Wang, Yifan Xu, An Yan, Chenyu Yang, Eting Yuan, Hanwen Zha, Nan Tang, Lei Chen, Nicolas Scheffer, Yue Liu, Nirav Shah, Rakesh Wanga, Anuj Kumar, Scott Yih, Xin Dong:
CRAG - Comprehensive RAG Benchmark. - Wenyu Du, Tongxu Luo, Zihan Qiu, Zeyu Huang, Yikang Shen, Reynold Cheng, Yike Guo, Jie Fu:
Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training. - David Perera, Victor Letzelter, Théo Mariotte, Adrien Cortés, Mickaël Chen, Slim Essid, Gaël Richard:
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing. - Jaeseok Jang, Hyuk-Yoon Kwon:
Are Multiple Instance Learning Algorithms Learnable for Instances? - Minseon Gwak, Seongrok Moon, Joohwan Ko, PooGyeon Park:
Layer-Adaptive State Pruning for Deep State Space Models. - Matthieu Kirchmeyer, Pedro O. Pinheiro, Saeed Saremi:
Score-based 3D molecule generation with neural fields. - Jiatong Li, Renjun Hu, Kunzhe Huang, Yan Zhuang, Qi Liu, Mengxiao Zhu, Xing Shi, Wei Lin:
PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbations. - Yongchun Li, Santanu Dey, Weijun Xie:
On Sparse Canonical Correlation Analysis. - Jiangyuan Li, Jiayi Wang, Raymond K. W. Wong, Kwun Chuen Gary Chan:
A Pairwise Pseudo-likelihood Approach for Matrix Completion with Informative Missingness. - Weihang Xu, Maryam Fazel, Simon S. Du:
Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models. - Elizabeth Louise Baker, Gefan Yang, Michael L. Severinsen, Christy Anna Hipsley, Stefan Sommer:
Conditioning non-linear and infinite-dimensional diffusion processes. - Yusu Hong, Junhong Lin:
On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions. - Po-Wei Huang, Patrick Rebentrost:
Quantum algorithm for large-scale market equilibrium computation. - David P. Woodruff, Samson Zhou:
Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters. - Roi Cohen, Konstantin Dobler, Eden Biran, Gerard de Melo:
I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token. - Gennaro Gala, Cassio P. de Campos, Antonio Vergari, Erik Quaeghebeur:
Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits. - Tuan Anh Pham, Vikas Garg:
What do Graph Neural Networks learn? Insights from Tropical Geometry. - Takeshi Koshizuka, Masahiro Fujisawa, Yusuke Tanaka, Issei Sato:
Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective. - Xuechen Zhang, Xiangyu Chang, Mingchen Li, Amit K. Roy-Chowdhury, Jiasi Chen, Samet Oymak:
Selective Attention: Enhancing Transformer through Principled Context Control. - Jeremiah Birrell, Reza Ebrahimi, Rouzbeh Behnia, Jason Pacheco:
Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement. - Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
A Simple and Optimal Approach for Universal Online Learning with Gradient Variations. - Xuexun Liu, Xiaoxu Xu, Jinlong Li, Qiudan Zhang, Xu Wang, Nicu Sebe, Lin Ma:
LESS: Label-Efficient and Single-Stage Referring 3D Segmentation. - Maryam Aliakbarpour, Piotr Indyk, Ronitt Rubinfeld, Sandeep Silwal:
Optimal Algorithms for Augmented Testing of Discrete Distributions. - Luca Barsellotti, Roberto Bigazzi, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara:
Personalized Instance-based Navigation Toward User-Specific Objects in Realistic Environments. - Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han:
Mind the Gap Between Prototypes and Images in Cross-domain Finetuning. - Ziyi Chen, Yan Wen, Zhengmian Hu, Heng Huang:
Robust Reinforcement Learning with General Utility. - Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder, Vianney Perchet:
Addressing Bias in Online Selection with Limited Budget of Comparisons. - Xueying Jiang, Sheng Jin, Xiaoqin Zhang, Ling Shao, Shijian Lu:
MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders. - Matt MacDermott, James Fox, Francesco Belardinelli, Tom Everitt:
Measuring Goal-Directedness. - Liwei Huang, Zhengyu Ma, Liutao Yu, Huihui Zhou, Yonghong Tian:
Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli. - Yijun Liu, Jiequan Cui, Zhuotao Tian, Senqiao Yang, Qingdong He, Xiaoling Wang, Jingyong Su:
Typicalness-Aware Learning for Failure Detection. - David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo, Santiago Góngora, Aishik Mandal, Sukannya Purkayastha, Jesús-Germán Ortiz-Barajas, Emilio Villa-Cueva, Jinheon Baek, Soyeong Jeong, Injy Hamed, Zheng Xin Yong, Zheng Wei Lim, Paula Mónica Silva, Jocelyn Dunstan, Mélanie Jouitteau, David Le Meur, Joan Nwatu, Ganzorig Batnasan, Munkh-Erdene Otgonbold, Munkhjargal Gochoo, Guido Ivetta, Luciana Benotti, Laura Alonso Alemany, Hernán Maina, Jiahui Geng, Tiago Timponi Torrent, Frederico Belcavello, Marcelo Viridiano, Jan Christian Blaise Cruz, Dan John Velasco, Oana Ignat, Zara Burzo, Chenxi Whitehouse, Artem Abzaliev, Teresa Clifford, Grainne Caulfield, Teresa Lynn, Christian Salamea Palacios, Vladimir Araujo, Yova Kementchedjhieva, Mihail Mihaylov, Israel Abebe Azime, Henok Biadglign Ademtew, Bontu Fufa Balcha, Naome A. Etori, David Ifeoluwa Adelani, Rada Mihalcea, Atnafu Lambebo Tonja, Maria Camila Buitrago Cabrera, Gisela Vallejo, Holy Lovenia, Ruochen Zhang, Marcos Estecha-Garitagoitia, Mario Rodríguez-Cantelar, Toqeer Ehsan, Rendi Chevi, Muhammad Farid Adilazuarda, Ryandito Diandaru, Samuel Cahyawijaya, Fajri Koto, Tatsuki Kuribayashi, Haiyue Song, Aditya Khandavally, Thanmay Jayakumar, Raj Dabre, Mohamed Fazli Mohamed Imam, Kumaranage Ravindu Yasas Nagasinghe, Alina Dragonetti, Luis Fernando D'Haro, Olivier Niyomugisha, Jay Gala, Pranjal A. Chitale, Fauzan Farooqui, Thamar Solorio, Alham Fikri Aji:
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark. - Dong Huang, Yuhao Qing, Weiyi Shang, Heming Cui, Jie Zhang:
EffiBench: Benchmarking the Efficiency of Automatically Generated Code. - George Tsoukalas, Jasper Lee, John Jennings, Jimmy Xin, Michelle Ding, Michael Jennings, Amitayush Thakur, Swarat Chaudhuri:
PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition. - Dongsu Lee, Minhae Kwon:
Episodic Future Thinking Mechanism for Multi-agent Reinforcement Learning. - Jindong Jiang, Fei Deng, Gautam Singh, Minseung Lee, Sungjin Ahn:
Slot State Space Models. - Yongwei Nie, Mingxian Fan, Chengjiang Long, Qing Zhang, Jian Zhu, Xuemiao Xu:
Incorporating Test-Time Optimization into Training with Dual Networks for Human Mesh Recovery. - Yu Xiang, Jie Qiao, Zefeng Liang, Zihuai Zeng, Ruichu Cai, Zhifeng Hao:
On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function. - Chunan Liu, Lilian Denzler, Yihong Chen, Andrew C. R. Martin, Brooks Paige:
AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction. - Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent:
Variational Flow Matching for Graph Generation. - Jaehee Kim, Yukyung Lee, Pilsung Kang:
A Gradient Accumulation Method for Dense Retriever under Memory Constraint. - Haicang Zhou, Weiming Huang, Yile Chen, Tiantian He, Gao Cong, Yew Soon Ong:
Road Network Representation Learning with the Third Law of Geography. - Haizhou Du, Yijian Chen, Ryan Yang, Yuchen Li, Linghe Kong:
HyperPrism: An Adaptive Non-linear Aggregation Framework for Distributed Machine Learning over Non-IID Data and Time-varying Communication Links. - Gwanghyun Kim, Alonso Martinez, Yu-Chuan Su, Brendan Jou, José Lezama, Agrim Gupta, Lijun Yu, Lu Jiang, Aren Jansen, Jacob Walker, Krishna Somandepalli:
A Versatile Diffusion Transformer with Mixture of Noise Levels for Audiovisual Generation. - Haoran Lu, Ruihai Wu, Yitong Li, Sijie Li, Ziyu Zhu, Chuanruo Ning, Yan Zhao, Longzan Luo, Yuanpei Chen, Hao Dong:
GarmentLab: A Unified Simulation and Benchmark for Garment Manipulation. - Hayden McTavish, Jon Donnelly, Margo I. Seltzer, Cynthia Rudin:
Interpretable Generalized Additive Models for Datasets with Missing Values. - Fangcheng Liu, Yehui Tang, Zhenhua Liu, Yunsheng Ni, Duyu Tang, Kai Han, Yunhe Wang:
Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exiting. - Yiwen Qiu, Yujia Zheng, Kun Zhang:
Identifying Selections for Unsupervised Subtask Discovery. - Barna Pásztor, Parnian Kassraie, Andreas Krause:
Bandits with Preference Feedback: A Stackelberg Game Perspective. - Sanghyun Son, Matheus Gadelha, Yang Zhou, Zexiang Xu, Ming C. Lin, Yi Zhou:
DMesh: A Differentiable Mesh Representation. - Jacob Silberg, Kyle Swanson, Elana Simon, Angela Zhang, Zaniar Ghazizadeh, Scott Ogden, Hisham Hamadeh, James Y. Zou:
UniTox: Leveraging LLMs to Curate a Unified Dataset of Drug-Induced Toxicity from FDA Labels. - Xingkui Zhu, Yiran Guan, Dingkang Liang, Yuchao Chen, Yuliang Liu, Xiang Bai:
MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision Tasks. - Rongzhe Wei, Eli Chien, Pan Li:
Differentially Private Graph Diffusion with Applications in Personalized PageRanks. - Jialin Luo, Yuanzhi Wang, Ziqi Gu, Yide Qiu, Shuaizhen Yao, Fuyun Wang, Chunyan Xu, Wenhua Zhang, Dan Wang, Zhen Cui:
MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generation. - Mingjia Li, Shuang Li, Tongrui Su, Longhui Yuan, Jian Liang, Wei Li:
Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation. - Wang Lin, Jingyuan Chen, Jiaxin Shi, Zirun Guo, Yichen Zhu, Zehan Wang, Tao Jin, Zhou Zhao, Fei Wu, Shuicheng Yan, Hanwang Zhang:
Action Imitation in Common Action Space for Customized Action Image Synthesis. - Xin Cai, Zhiyuan You, Hailong Zhang, Jinwei Gu, Wentao Liu, Tianfan Xue:
PhoCoLens: Photorealistic and Consistent Reconstruction in Lensless Imaging. - Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun:
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage. - Delin Qu, Qizhi Chen, Pingrui Zhang, Xianqiang Gao, Bin Zhao, Zhigang Wang, Dong Wang, Xuelong Li:
LiveScene: Language Embedding Interactive Radiance Fields for Physical Scene Control and Rendering. - Kairan Zhao, Meghdad Kurmanji, George-Octavian Barbulescu, Eleni Triantafillou, Peter Triantafillou:
What makes unlearning hard and what to do about it. - Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin:
The Power of Resets in Online Reinforcement Learning. - Sergey Samsonov, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov:
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning. - Hao Bai, Yifei Zhou, Jiayi Pan, Mert Cemri, Alane Suhr, Sergey Levine, Aviral Kumar:
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning. - Nikita Starodubcev, Mikhail Khoroshikh, Artem Babenko, Dmitry Baranchuk:
Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps. - Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet:
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms. - Jiabao Ji, Yujian Liu, Yang Zhang, Gaowen Liu, Ramana Kompella, Sijia Liu, Shiyu Chang:
Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference. - Lei Zhu, Fangyun Wei, Yanye Lu, Dong Chen:
Scaling the Codebook Size of VQ-GAN to 100, 000 with a Utilization Rate of 99%. - Domenic Rosati, Jan Wehner, Kai Williams, Lukasz Bartoszcze, Robie Gonzales, Carsten Maple, Subhabrata Majumdar, Hassan Sajjad, Frank Rudzicz:
Representation Noising: A Defence Mechanism Against Harmful Finetuning. - Changdae Oh, Hyesu Lim, Mijoo Kim, Dongyoon Han, Sangdoo Yun, Jaegul Choo, Alexander Hauptmann, Zhi-Qi Cheng, Kyungwoo Song:
Towards Calibrated Robust Fine-Tuning of Vision-Language Models. - Peiran Dong, Bingjie Wang, Song Guo, Junxiao Wang, Jie Zhang, Zicong Hong:
Towards Safe Concept Transfer of Multi-Modal Diffusion via Causal Representation Editing. - Hongyi Zhou, Denis Blessing, Ge Li, Onur Celik, Xiaogang Jia, Gerhard Neumann, Rudolf Lioutikov:
Variational Distillation of Diffusion Policies into Mixture of Experts. - Peng Tan, Hai-Tian Liu, Zhi-Hao Tan, Zhi-Hua Zhou:
Handling Learnwares from Heterogeneous Feature Spaces with Explicit Label Exploitation. - Woosung Kim, Hayeong Lee, Jongmin Lee, Byung-Jun Lee:
ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making. - Shinsaku Sakaue, Taihei Oki:
Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming. - Sijie Zhao, Yong Zhang, Xiaodong Cun, Shaoshu Yang, Muyao Niu, Xiaoyu Li, Wenbo Hu, Ying Shan:
CV-VAE: A Compatible Video VAE for Latent Generative Video Models. - Jingyi Zhang, Jiaxing Huang, Xiaoqin Zhang, Ling Shao, Shijian Lu:
Historical Test-time Prompt Tuning for Vision Foundation Models. - Sobihan Surendran, Adeline Fermanian, Antoine Godichon-Baggioni, Sylvain Le Corff:
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation. - Keegan Harris, Zhiwei Steven Wu, Maria-Florina Balcan:
Regret Minimization in Stackelberg Games with Side Information. - Haiyang Huang, Yingfan Wang, Cynthia Rudin:
Navigating the Effect of Parametrization for Dimensionality Reduction. - Yuqi Wang, Ke Cheng, Jiawei He, Qitai Wang, Hengchen Dai, Yuntao Chen, Fei Xia, Zhao-Xiang Zhang:
DrivingDojo Dataset: Advancing Interactive and Knowledge-Enriched Driving World Model. - Qiang Wu, Gechang Yao, Zhixi Feng, Shuyuan Yang:
Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis. - Chenlin Zhou, Han Zhang, Zhaokun Zhou, Liutao Yu, Liwei Huang, Xiaopeng Fan, Li Yuan, Zhengyu Ma, Huihui Zhou, Yonghong Tian:
QKFormer: Hierarchical Spiking Transformer using Q-K Attention. - Yongzhe Jia, Xuyun Zhang, Hongsheng Hu, Kim-Kwang Raymond Choo, Lianyong Qi, Xiaolong Xu, Amin Beheshti, Wanchun Dou:
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices. - Miles Hutson, Isaac Kauvar, Nick Haber:
Policy-shaped prediction: avoiding distractions in model-based reinforcement learning. - Pham Duy Khanh, Hoang-Chau Luong, Boris S. Mordukhovich, Dat Ba Tran:
Fundamental Convergence Analysis of Sharpness-Aware Minimization. - Ariel D. Procaccia, Ben Schiffer, Shirley Zhang:
Honor Among Bandits: No-Regret Learning for Online Fair Division. - Boris Repasky, Ehsan Abbasnejad, Anthony R. Dick:
BLURD: Benchmarking and Learning using a Unified Rendering and Diffusion Model. - Tianyu He, Darshil Doshi, Aritra Das, Andrey Gromov:
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks. - Hanyue Lou, Jinxiu (Sherry) Liang, Minggui Teng, Bin Fan, Yong Xu, Boxin Shi:
Zero-Shot Event-Intensity Asymmetric Stereo via Visual Prompting from Image Domain. - Junyu Lu, Bo Xu, Xiaokun Zhang, Hongbo Wang, Haohao Zhu, Dongyu Zhang, Liang Yang, Hongfei Lin:
Towards Comprehensive Detection of Chinese Harmful Memes. - Tariq Berrada Ifriqi, Pietro Astolfi, Melissa Hall, Reyhane Askari Hemmat, Yohann Benchetrit, Marton Havasi, Matthew J. Muckley, Karteek Alahari, Adriana Romero-Soriano, Jakob Verbeek, Michal Drozdzal:
On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. - Xinyu Zhao, Guoheng Sun, Ruisi Cai, Yukun Zhou, Pingzhi Li, Peihao Wang, Bowen Tan, Yexiao He, Li Chen, Yi Liang, Beidi Chen, Binhang Yuan, Hongyi Wang, Ang Li, Zhangyang Wang, Tianlong Chen:
Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild. - Peng Wang, Songshuo Lu, Yaohua Tang, Sijie Yan, Wei Xia, Yuanjun Xiong:
A Full-duplex Speech Dialogue Scheme Based On Large Language Model. - Takeshi Noda, Chao Chen, Weiqi Zhang, Xinhai Liu, Yu-Shen Liu, Zhizhong Han:
MultiPull: Detailing Signed Distance Functions by Pulling Multi-Level Queries at Multi-Step. - Hongzhi Ruan, Haibao Yu, Wenxian Yang, Siqi Fan, Zaiqing Nie:
Learning Cooperative Trajectory Representations for Motion Forecasting. - Matthew Dowling, Yuan Zhao, Memming Park:
eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modeling. - Louis Serrano, Thomas X. Wang, Etienne Le Naour, Jean-Noël Vittaut, Patrick Gallinari:
AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields. - Hang Guo, Tao Dai, Yuanchao Bai, Bin Chen, Xudong Ren, Zexuan Zhu, Shu-Tao Xia:
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts. - Paul Couairon, Mustafa Shukor, Jean-Emmanuel Haugeard, Matthieu Cord, Nicolas Thome:
DiffCut: Catalyzing Zero-Shot Semantic Segmentation with Diffusion Features and Recursive Normalized Cut. - James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai:
BitDelta: Your Fine-Tune May Only Be Worth One Bit. - Zhe Liu, Jinghua Hou, Xinyu Wang, Xiaoqing Ye, Jingdong Wang, Hengshuang Zhao, Xiang Bai:
LION: Linear Group RNN for 3D Object Detection in Point Clouds. - Yinshuang Xu, Dian Chen, Katherine Liu, Sergey Zakharov, Rares Ambrus, Kostas Daniilidis, Vitor Guizilini:
$SE(3)$ Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation. - Zheng Zhan, Yushu Wu, Yifan Gong, Zichong Meng, Zhenglun Kong, Changdi Yang, Geng Yuan, Pu Zhao, Wei Niu, Yanzhi Wang:
Fast and Memory-Efficient Video Diffusion Using Streamlined Inference. - Kartikeya Bhardwaj, Nilesh Prasad Pandey, Sweta Priyadarshi, Viswanath Ganapathy, Shreya Kadambi, Rafael Esteves, Shubhankar Borse, Paul N. Whatmough, Risheek Garrepalli, Mart van Baalen, Harris Teague, Markus Nagel:
Sparse High Rank Adapters. - Nithish Kannen, Arif Ahmad, Marco Andreetto, Vinodkumar Prabhakaran, Utsav Prabhu, Adji Bousso Dieng, Pushpak Bhattacharyya, Shachi Dave:
Beyond Aesthetics: Cultural Competence in Text-to-Image Models. - Jeonghwan Cheon, Sang Wan Lee, Se-Bum Paik:
Pretraining with Random Noise for Fast and Robust Learning without Weight Transport. - Quanling Meng, Qinglin Liu, Zonglin Li, Xiangyuan Lan, Shengping Zhang, Liqiang Nie:
High-Resolution Image Harmonization with Adaptive-Interval Color Transformation. - Yuhui Quan, Tianxiang Zheng, Hui Ji:
Pseudo-Siamese Blind-spot Transformers for Self-Supervised Real-World Denoising. - Marcel Kollovieh, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann:
Expected Probabilistic Hierarchies. - Seon-Ho Lee, Jue Wang, Zhikang Zhang, David Fan, Xinyu Li:
Video Token Merging for Long Video Understanding. - Juhao Liang, Zhenyang Cai, Jianqing Zhu, Huang Huang, Kewei Zong, Bang An, Mosen Alharthi, Juncai He, Lian Zhang, Haizhou Li, Benyou Wang, Jinchao Xu:
Alignment at Pre-training! Towards Native Alignment for Arabic LLMs. - Tristan Cinquin, Marvin Pförtner, Vincent Fortuin, Philipp Hennig, Robert Bamler:
FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning. - Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines:
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning. - Ziyi Liu, Idan Attias, Dan Roy:
Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood. - Ieva Petrulionyte, Julien Mairal, Michael Arbel:
Functional Bilevel Optimization for Machine Learning. - Zhezhe Jiao, Martin Keller-Ressel:
Emergence of heavy tails in homogenized stochastic gradient descent. - Zhongwang Zhang, Pengxiao Lin, Zhiwei Wang, Yaoyu Zhang, Zhi-Qin John Xu:
Initialization is Critical to Whether Transformers Fit Composite Functions by Reasoning or Memorizing. - Xuan Huang, Hanhui Li, Wanquan Liu, Xiaodan Liang, Yiqiang Yan, Yuhao Cheng, Chenqiang Gao:
Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars. - Arpit Agarwal, Eric Balkanski:
Learning-Augmented Dynamic Submodular Maximization. - Xinping Chen, Xiao Ke, Wenzhong Guo:
IF-Font: Ideographic Description Sequence-Following Font Generation. - Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. - Xiaobin Li, Kai Wu, Yujian Betterest Li, Xiaoyu Zhang, Handing Wang, Jing Liu:
Pretrained Optimization Model for Zero-Shot Black Box Optimization. - Alex Jinpeng Wang, Linjie Li, Yiqi Lin, Min Li, Lijuan Wang, Mike Zheng Shou:
Leveraging Visual Tokens for Extended Text Contexts in Multi-Modal Learning. - Ruihao Zheng, Zhenkun Wang:
Boundary Decomposition for Nadir Objective Vector Estimation. - Steven D. Morad, Chris Lu, Ryan Kortvelesy, Stephan Liwicki, Jakob N. Foerster, Amanda Prorok:
Recurrent Reinforcement Learning with Memoroids. - Wenhao Wang, Yifan Sun, Zhentao Tan, Yi Yang:
Image Copy Detection for Diffusion Models. - Jiamu Bai, Daoyuan Chen, Bingchen Qian, Liuyi Yao, Yaliang Li:
Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources. - Egor Gladin, Pavel E. Dvurechenskii, Alexander Mielke, Jia-Jie Zhu:
Interaction-Force Transport Gradient Flows. - Junxi Xiao, Qinliang Su:
TreeVI: Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing. - Arthur da Cunha, Mikael Møller Høgsgaard, Kasper Green Larsen:
Optimal Parallelization of Boosting. - Tianyi Qiu, Yang Zhang, Xuchuan Huang, Jasmine Xinze Li, Jiaming Ji, Yaodong Yang:
ProgressGym: Alignment with a Millennium of Moral Progress. - Thomas Kwa, Drake Thomas, Adrià Garriga-Alonso:
Catastrophic Goodhart: regularizing RLHF with KL divergence does not mitigate heavy-tailed reward misspecification. - Xingchi Li, Guanxun Li, Xianyang Zhang:
Segmenting Watermarked Texts From Language Models. - Alaia Solko-Breslin, Seewon Choi, Ziyang Li, Neelay Velingker, Rajeev Alur, Mayur Naik, Eric Wong:
Data-Efficient Learning with Neural Programs. - Yuan He, Moy Yuan, Jiaoyan Chen, Ian Horrocks:
Language Models as Hierarchy Encoders. - Shivang Rawat, David J. Heeger, Stefano Martiniani:
Unconditional stability of a recurrent neural circuit implementing divisive normalization. - Che Liu, Cheng Ouyang, Sibo Cheng, Anand Shah, Wenjia Bai, Rossella Arcucci:
G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training. - Xinyi Wu, Amir Ajorlou, Yifei Wang, Stefanie Jegelka, Ali Jadbabaie:
On the Role of Attention Masks and LayerNorm in Transformers. - Aaron Mishkin, Ahmed Khaled, Yuanhao Wang, Aaron Defazio, Robert M. Gower:
Directional Smoothness and Gradient Methods: Convergence and Adaptivity. - Haiji Liang, Ruize Han:
OVT-B: A New Large-Scale Benchmark for Open-Vocabulary Multi-Object Tracking. - Yang Xu, Yihong Gu, Cong Fang:
The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing. - Xiaokun Feng, Xuchen Li, Shiyu Hu, Dailing Zhang, Meiqi Wu, Jing Zhang, Xiaotang Chen, Kaiqi Huang:
MemVLT: Vision-Language Tracking with Adaptive Memory-based Prompts. - Mingrui Zhang, Chunyang Wang, Stephan C. Kramer, Joseph G. Wallwork, Siyi Li, Jiancheng Liu, Xiang Chen, Matthew D. Piggott:
Towards Universal Mesh Movement Networks. - Guang-Yuan Hao, Jiji Zhang, Biwei Huang, Hao Wang, Kun Zhang:
Natural Counterfactuals With Necessary Backtracking. - Changwoo Lee, Soo Min Kwon, Qing Qu, Hun-Seok Kim:
BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference. - Yiping Wang, Yifang Chen, Wendan Yan, Alex Fang, Wenjing Zhou, Kevin Jamieson, Simon S. Du:
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning. - Xiaoxing Wang, Xiaohan Qin, Xiaokang Yang, Junchi Yan:
ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization. - Shengyuan Chen, Qinggang Zhang, Junnan Dong, Wen Hua, Qing Li, Xiao Huang:
Entity Alignment with Noisy Annotations from Large Language Models. - Qiyao Liang, Ziming Liu, Mitchell Ostrow, Ila Fiete:
How Diffusion Models Learn to Factorize and Compose. - Antoine Scheid, Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Durmus:
Learning to Mitigate Externalities: the Coase Theorem with Hindsight Rationality. - Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang, Fabian Isensee, Zifu Wang, Jieneng Chen, Yu-Cheng Chou, Yannick Kirchhoff, Maximilian Rokuss, Ziyan Huang, Jin Ye, Junjun He, Tassilo Wald, Constantin Ulrich, Michael Baumgartner, Saikat Roy, Klaus H. Maier-Hein, Paul F. Jaeger, Yiwen Ye, Yutong Xie, Jianpeng Zhang, Ziyang Chen, Yong Xia, Zhaohu Xing, Lei Zhu, Yousef Sadegheih, Afshin Bozorgpour, Pratibha Kumari, Reza Azad, Dorit Merhof, Pengcheng Shi, Ting Ma, Yuxin Du, Fan Bai, Tiejun Huang, Bo Zhao, Haonan Wang, Xiaomeng Li, Hanxue Gu, Haoyu Dong, Jichen Yang, Maciej A. Mazurowski, Saumya Gupta, Linshan Wu, Jia-Xin Zhuang, Hao Chen, Holger Roth, Daguang Xu, Matthew B. Blaschko, Sergio Decherchi, Andrea Cavalli, Alan L. Yuille, Zongwei Zhou:
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation? - Rongzhen Wang, Chenyu Zheng, Guoqiang Wu, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li:
Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization. - Taejong Joo, Diego Klabjan:
Improving self-training under distribution shifts via anchored confidence with theoretical guarantees. - Haiyu Zhang, Xinyuan Chen, Yaohui Wang, Xihui Liu, Yunhong Wang, Yu Qiao:
4Diffusion: Multi-view Video Diffusion Model for 4D Generation. - Yiran Zhao, Wenxuan Zhang, Guizhen Chen, Kenji Kawaguchi, Lidong Bing:
How do Large Language Models Handle Multilingualism? - Hongyao Tang, Glen Berseth:
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn. - Fanghua Ye, Mingming Yang, Jianhui Pang, Longyue Wang, Derek F. Wong, Emine Yilmaz, Shuming Shi, Zhaopeng Tu:
Benchmarking LLMs via Uncertainty Quantification. - Walter Simoncini, Andrei Bursuc, Spyridon Gidaris, Yuki M. Asano:
No Train, all Gain: Self-Supervised Gradients Improve Deep Frozen Representations. - Zihan Liu, Wei Ping, Rajarshi Roy, Peng Xu, Chankyu Lee, Mohammad Shoeybi, Bryan Catanzaro:
ChatQA: Surpassing GPT-4 on Conversational QA and RAG. - Jihao Andreas Lin, Shreyas Padhy, Bruno Mlodozeniec, Javier Antorán, José Miguel Hernández-Lobato:
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes. - Hao Ma, Tianyi Hu, Zhiqiang Pu, Boyin Liu, Xiaolin Ai, Yanyan Liang, Min Chen:
Coevolving with the Other You: Fine-Tuning LLM with Sequential Cooperative Multi-Agent Reinforcement Learning. - Austin Coursey, Junyi Ji, Marcos Quiñones-Grueiro, William Barbour, Yuhang Zhang, Tyler Derr, Gautam Biswas, Daniel B. Work:
FT-AED: Benchmark Dataset for Early Freeway Traffic Anomalous Event Detection. - Diba Hashemi, Lie He, Martin Jaggi:
CoBo: Collaborative Learning via Bilevel Optimization. - Xiao Tan, Yiqin Wang, Yangyang Shen, Dian Shen, Meng Wang, Peibo Duan, Beilun Wang:
FasMe: Fast and Sample-efficient Meta Estimator for Precision Matrix Learning in Small Sample Settings. - Shraddha Barke, Emmanuel Anaya Gonzalez, Saketh Ram Kasibatla, Taylor Berg-Kirkpatrick, Nadia Polikarpova:
HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis. - Anshul Gupta, Samy Tafasca, Arya Farkhondeh, Pierre Vuillecard, Jean-Marc Odobez:
MTGS: A Novel Framework for Multi-Person Temporal Gaze Following and Social Gaze Prediction. - Chengxing Xie, Canyu Chen, Feiran Jia, Ziyu Ye, Shiyang Lai, Kai Shu, Jindong Gu, Adel Bibi, Ziniu Hu, David Jurgens, James Evans, Philip Torr, Bernard Ghanem, Guohao Li:
Can Large Language Model Agents Simulate Human Trust Behavior? - Yuxin Xiao, Chaoqun Wan, Yonggang Zhang, Wenxiao Wang, Binbin Lin, Xiaofei He, Xu Shen, Jieping Ye:
Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control. - Pragya Singh, Ritvik Budhiraja, Ankush Gupta, Anshul Goswami, Mohan Kumar, Pushpendra Singh:
EEVR: A Dataset of Paired Physiological Signals and Textual Descriptions for Joint Emotion Representation Learning. - Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Joanna Matthiesen, Kevin A. Smith, Josh Tenenbaum:
Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads. - Xiaoyue Xu, Qinyuan Ye, Xiang Ren:
Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack. - Yangjun Ruan, Chris J. Maddison, Tatsunori B. Hashimoto:
Observational Scaling Laws and the Predictability of Langauge Model Performance. - Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Lior Shani, Yi Liang, Craig Boutilier:
Embedding-Aligned Language Models. - Richard Nock, Yishay Mansour:
How to Boost Any Loss Function. - Harit Vishwakarma, Yi Chen, Sui Jiet Tay, Satya Sai Srinath Namburi, Frederic Sala, Ramya Korlakai Vinayak:
Pearls from Pebbles: Improved Confidence Functions for Auto-labeling. - Zhaoyang Sun, Shengwu Xiong, Yaxiong Chen, Fei Du, Weihua Chen, Fan Wang, Yi Rong:
SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Models. - Li Ma, Haoyu Han, Juanhui Li, Harry Shomer, Hui Liu, Xiaofeng Gao, Jiliang Tang:
Mixture of Link Predictors on Graphs. - Alexander Rutherford, Michael Beukman, Timon Willi, Bruno Lacerda, Nick Hawes, Jakob N. Foerster:
No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery. - Raj Agrawal, Sam Witty, Andy Zane, Elias Bingham:
Automated Efficient Estimation using Monte Carlo Efficient Influence Functions. - Xiayan Ji, Anton Xue, Eric Wong, Oleg Sokolsky, Insup Lee:
AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties. - Kaibo Zhang, Yunjuan Wang, Raman Arora:
Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation. - Xiao Yu, Yuang Qi, Kejiang Chen, Guoqiang Chen, Xi Yang, Pengyuan Zhu, Xiuwei Shang, Weiming Zhang, Nenghai Yu:
DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection. - Rakshit S. Trivedi, Akbir Khan, Jesse Clifton, Lewis Hammond, Edgar A. Duéñez-Guzmán, Dipam Chakraborty, John P. Agapiou, Jayd Matyas, Alexander Sasha Vezhnevets, Barna Pásztor, Yunke Ao, Omar G. Younis, Jiawei Huang, Benjamin Swain, Haoyuan Qin, Mian Deng, Ziwei Deng, Utku Erdoganaras, Yue Zhao, Marko Tesic, Natasha Jaques, Jakob N. Foerster, Vincent Conitzer, José Hernández-Orallo, Dylan Hadfield-Menell, Joel Z. Leibo:
Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence. - Zhengfei Kuang, Shengqu Cai, Hao He, Yinghao Xu, Hongsheng Li, Leonidas J. Guibas, Gordon Wetzstein:
Collaborative Video Diffusion: Consistent Multi-video Generation with Camera Control. - Hee Jae Kim, Kathakoli Sengupta, Masaki Kuribayashi, Hernisa Kacorri, Eshed Ohn-Bar:
Text to Blind Motion. - Min Jae Song:
Cryptographic Hardness of Score Estimation. - Alexander Braun, Sherry Sarkar:
The Secretary Problem with Predicted Additive Gap. - Ruslan Svirschevski, Avner May, Zhuoming Chen, Beidi Chen, Zhihao Jia, Max Ryabinin:
SpecExec: Massively Parallel Speculative Decoding For Interactive LLM Inference on Consumer Devices. - Kevin Christian Wibisono, Yixin Wang:
From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When. - Lingao Xiao, Yang He:
Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation? - Chenghua Guo, Han Yu, Jiaxin Liu, Chao Chen, Qi Li, Sihong Xie, Xi Zhang:
Linear Uncertainty Quantification of Graphical Model Inference. - Elliot Paquette, Courtney Paquette, Lechao Xiao, Jeffrey Pennington:
4+3 Phases of Compute-Optimal Neural Scaling Laws. - Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler:
Learning Mixtures of Unknown Causal Interventions. - Hongfu Gao, Feipeng Zhang, Wenyu Jiang, Jun Shu, Feng Zheng, Hongxin Wei:
On the Noise Robustness of In-Context Learning for Text Generation. - Mingzhe Du, Anh Tuan Luu, Bin Ji, Qian Liu, See-Kiong Ng:
Mercury: A Code Efficiency Benchmark for Code Large Language Models. - Tianwei Xiong, Yuqing Wang, Daquan Zhou, Zhijie Lin, Jiashi Feng, Xihui Liu:
LVD-2M: A Long-take Video Dataset with Temporally Dense Captions. - Tongle Wu, Ying Sun:
Implicit Regularization of Decentralized Gradient Descent for Sparse Regression. - Prajwal Singhania, Siddharth Singh, Shwai He, Soheil Feizi, Abhinav Bhatele:
Loki: Low-rank Keys for Efficient Sparse Attention. - Yang Li, Shaobo Han, Shihao Ji:
VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks. - Hanchen Xia, Weidong Liu, Xiaojun Mao:
ST$_k$: A Scalable Module for Solving Top-k Problems. - Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams, Petrus Mikkola, Marcelo Hartmann, Kai Puolamäki, Arto Klami:
Non-geodesically-convex optimization in the Wasserstein space. - Qiujiang Jin, Ruichen Jiang, Aryan Mokhtari:
Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search. - Shen Li, Yuyang Zhang, Zhaolin Ren, Claire Liang, Na Li, Julie A. Shah:
Enhancing Preference-based Linear Bandits via Human Response Time. - Scott R. Jeen, Tom Bewley, Jonathan M. Cullen:
Zero-Shot Reinforcement Learning from Low Quality Data. - Chang-Wei Shi, Yi-Rui Yang, Wu-Jun Li:
Ordered Momentum for Asynchronous SGD. - Amir Hossein Kargaran, François Yvon, Hinrich Schütze:
GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages. - Esraa Elelimy, Adam White, Michael Bowling, Martha White:
Real-Time Recurrent Learning using Trace Units in Reinforcement Learning. - Baiqi Li, Zhiqiu Lin, Wenxuan Peng, Jean de Dieu Nyandwi, Daniel Jiang, Zixian Ma, Simran Khanuja, Ranjay Krishna, Graham Neubig, Deva Ramanan:
NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples. - Shreyas Chaudhari, Ameet Deshpande, Bruno C. da Silva, Philip S. Thomas:
Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation. - Jiahao Ying, Yixin Cao, Yushi Bai, Qianru Sun, Bo Wang, Wei Tang, Zhaojun Ding, Yizhe Yang, Xuanjing Huang, Shuicheng Yan:
Automating Dataset Updates Towards Reliable and Timely Evaluation of Large Language Models. - Yizun Lin, Zhao-Rong Lai, Cheng Li:
A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization. - Juntao Dai, Tianle Chen, Xuyao Wang, Ziran Yang, Taiye Chen, Jiaming Ji, Yaodong Yang:
SafeSora: Towards Safety Alignment of Text2Video Generation via a Human Preference Dataset. - Yannis Karmim, Marc Lafon, Raphaël Fournier-S'niehotta, Nicolas Thome:
Supra-Laplacian Encoding for Transformer on Dynamic Graphs. - Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll, Costas J. Spanos, Adam Wierman, Ming Jin:
Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation. - Daehee Lee, Minjong Yoo, Woo Kyung Kim, Wonje Choi, Honguk Woo:
Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation. - Apurv Shukla, Debabrota Basu:
Preference-based Pure Exploration. - Zhongchang Sun, Sihong He, Fei Miao, Shaofeng Zou:
Policy Optimization for Robust Average Reward MDPs. - Jiaxu Leng, Zhanjie Wu, Mingpi Tan, Yiran Liu, Ji Gan, Haosheng Chen, Xinbo Gao:
Beyond Euclidean: Dual-Space Representation Learning for Weakly Supervised Video Violence Detection. - Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang:
Learning Discrete Latent Variable Structures with Tensor Rank Conditions. - Christopher Blöcker, Chester Tan, Ingo Scholtes:
The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks. - Jianan Yang, Chenchao Gao, Zhiqing Xiao, Junbo Zhao, Sai Wu, Gang Chen, Haobo Wang:
Locating What You Need: Towards Adapting Diffusion Models to OOD Concepts In-the-Wild. - Charbel Sakr, Brucek Khailany:
ESPACE: Dimensionality Reduction of Activations for Model Compression. - Zhanhao Hu, Julien Piet, Geng Zhao, Jiantao Jiao, David A. Wagner:
Toxicity Detection for Free. - Fei Ni, Jianye Hao, Shiguang Wu, Longxin Kou, Yifu Yuan, Zibin Dong, Jinyi Liu, Mingzhi Li, Yuzheng Zhuang, Yan Zheng:
PERIA: Perceive, Reason, Imagine, Act via Holistic Language and Vision Planning for Manipulation. - Yigit Ekin, Ahmet Burak Yildirim, Erdem Eren Caglar, Aykut Erdem, Erkut Erdem, Aysegul Dundar:
CLIPAway: Harmonizing focused embeddings for removing objects via diffusion models. - Nikita P. Kalinin, Christoph H. Lampert:
Banded Square Root Matrix Factorization for Differentially Private Model Training. - Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu:
Bayesian-guided Label Mapping for Visual Reprogramming. - Haogeng Liu, Quanzeng You, Xiaotian Han, Yongfei Liu, Huaibo Huang, Ran He, Hongxia Yang:
Visual Anchors Are Strong Information Aggregators For Multimodal Large Language Model. - Max Hamilton, Christian Lange, Elijah Cole, Alexander Shepard, Samuel Heinrich, Oisin Mac Aodha, Grant Van Horn, Subhransu Maji:
Combining Observational Data and Language for Species Range Estimation. - Matthew Wallingford, Anand Bhattad, Aditya Kusupati, Vivek Ramanujan, Matt Deitke, Aniruddha Kembhavi, Roozbeh Mottaghi, Wei-Chiu Ma, Ali Farhadi:
From an Image to a Scene: Learning to Imagine the World from a Million 360° Videos. - Juexiao Zhang, Gao Zhu, Sihang Li, Xinhao Liu, Haorui Song, Xinran Tang, Chen Feng:
Multiview Scene Graph. - Kyoungseok Jang, Junpei Komiyama, Kazutoshi Yamazaki:
Fixed Confidence Best Arm Identification in the Bayesian Setting. - Xiaojuan Tang, Jiaqi Li, Yitao Liang, Song-Chun Zhu, Muhan Zhang, Zilong Zheng:
Mars: Situated Inductive Reasoning in an Open-World Environment. - Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Qi Long, Li Shen:
Fairness-Aware Estimation of Graphical Models. - Jiawei Chen, Chunhui Zhao:
Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment. - Yi-Shan Wu, Yijie Zhang, Badr-Eddine Chérief-Abdellatif, Yevgeny Seldin:
Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss. - Sri Harsha Dumpala, Aman Jaiswal, Chandramouli Shama Sastry, Evangelos E. Milios, Sageev Oore, Hassan Sajjad:
SUGARCREPE++ Dataset: Vision-Language Model Sensitivity to Semantic and Lexical Alterations. - Sangyun Shin, Yuhang He, Madhu Vankadari, Ta Ying Cheng, Qian Xie, Andrew Markham, Niki Trigoni:
Towards Learning Group-Equivariant Features for Domain Adaptive 3D Detection. - Dingshuo Chen, Zhixun Li, Yuyan Ni, Guibin Zhang, Ding Wang, Qiang Liu, Shu Wu, Jeffrey Xu Yu, Liang Wang:
Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization. - Yilun Jin, Zheng Li, Chenwei Zhang, Tianyu Cao, Yifan Gao, Pratik Jayarao, Mao Li, Xin Liu, Ritesh Sarkhel, Xianfeng Tang, Haodong Wang, Zhengyang Wang, Wenju Xu, Jingfeng Yang, Qingyu Yin, Xian Li, Priyanka Nigam, Yi Xu, Kai Chen, Qiang Yang, Meng Jiang, Bing Yin:
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models. - Minui Hong, Junhyeog Yun, Insu Jeon, Gunhee Kim:
FedAvP: Augment Local Data via Shared Policy in Federated Learning. - Diego Doimo, Alessandro Serra, Alessio Ansuini, Alberto Cazzaniga:
The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models. - Zhaorui Tan, Xi Yang, Qiufeng Wang, Anh Nguyen, Kaizhu Huang:
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual Classification. - Yeonguk Yu, Minhwan Ko, Sungho Shin, Kangmin Kim, Kyoobin Lee:
Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise. - Matthijs Pals, A Erdem Sagtekin, Felix Pei, Manuel Glöckler, Jakob H. Macke:
Inferring stochastic low-rank recurrent neural networks from neural data. - Corinna Cortes, Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong:
Cardinality-Aware Set Prediction and Top-$k$ Classification. - Ruiqi Zhang, Jingfeng Wu, Peter L. Bartlett:
In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization. - Xin Hu, Xiaole Tang, Ruixuan Yu, Jian Sun:
Learning 3D Equivariant Implicit Function with Patch-Level Pose-Invariant Representation. - Bo Liu, Lemeng Wu, Lizhang Chen, Kaizhao Liang, Jiaxu Zhu, Chen Liang, Raghuraman Krishnamoorthi, Qiang Liu:
Communication Efficient Distributed Training with Distributed Lion. - MohammadTaghi Hajiaghayi, Shayan Chashm Jahan, Mohammad Sharifi, Suho Shin, Max Springer:
Fairness and Efficiency in Online Class Matching. - MohammadTaghi Hajiaghayi, Sébastien Lahaie, Keivan Rezaei, Suho Shin:
Ad Auctions for LLMs via Retrieval Augmented Generation. - Chong Mou, Mingdeng Cao, Xintao Wang, Zhaoyang Zhang, Ying Shan, Jian Zhang:
ReVideo: Remake a Video with Motion and Content Control. - Adithya Bhaskar, Alexander Wettig, Dan Friedman, Danqi Chen:
Finding Transformer Circuits With Edge Pruning. - Xiaotong Li, Fan Zhang, Haiwen Diao, Yueze Wang, Xinlong Wang, Lingyu Duan:
DenseFusion-1M: Merging Vision Experts for Comprehensive Multimodal Perception. - Declan McNamara, Jackson Loper, Jeffrey Regier:
Globally Convergent Variational Inference. - Robi Bhattacharjee, Ulrike von Luxburg:
Auditing Local Explanations is Hard. - Xinyu Xu, Yizheng Zhang, Yonglu Li, Lei Han, Cewu Lu:
HumanVLA: Towards Vision-Language Directed Object Rearrangement by Physical Humanoid. - Samin Yeasar Arnob, Riyasat Ohib, Sergey M. Plis, Amy Zhang, Alessandro Sordoni, Doina Precup:
Efficient Reinforcement Learning by Discovering Neural Pathways. - Jonathan Roberts, Kai Han, Neil Houlsby, Samuel Albanie:
SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation. - Megan Tjandrasuwita, Jie Xu, Armando Solar-Lezama, Wojciech Matusik:
MeMo: Meaningful, Modular Controllers via Noise Injection. - Lisha Chen, A. F. M. Saif, Yanning Shen, Tianyi Chen:
FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning. - Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Carlee Joe-Wong, Gina C. Adam, Nathaniel D. Bastian, Tian Lan:
RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space. - Eva Giboulot, Teddy Furon:
WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off. - Daeho Um, Ji Won Yoon, Seong-Jin Ahn, Yunha Yeo:
Gene-Gene Relationship Modeling Based on Genetic Evidence for Single-Cell RNA-Seq Data Imputation. - Benyuan Meng, Qianqian Xu, Zitai Wang, Zhiyong Yang, Xiaochun Cao, Qingming Huang:
Suppress Content Shift: Better Diffusion Features via Off-the-Shelf Generation Techniques. - Xiong-Hui Chen, Ziyan Wang, Yali Du, Shengyi Jiang, Meng Fang, Yang Yu, Jun Wang:
Policy Learning from Tutorial Books via Understanding, Rehearsing and Introspecting. - Ismail Alkhouri, Shijun Liang, Evan Bell, Qing Qu, Rongrong Wang, Saiprasad Ravishankar:
Image Reconstruction Via Autoencoding Sequential Deep Image Prior. - Aleksandros Sobczyk, Marko Mladenovic, Mathieu Luisier:
Invariant subspaces and PCA in nearly matrix multiplication time. - Chaolong Ying, Xinjian Zhao, Tianshu Yu:
Boosting Graph Pooling with Persistent Homology. - Yanmin Wu, Jiarui Meng, Haijie Li, Chenming Wu, Yahao Shi, Xinhua Cheng, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang, Jian Zhang:
OpenGaussian: Towards Point-Level 3D Gaussian-based Open Vocabulary Understanding. - Ioannis Caragiannis, Evi Micha, Nisarg Shah:
Proportional Fairness in Non-Centroid Clustering. - Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon:
PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher. - Zhen Huang, Zengzhi Wang, Shijie Xia, Xuefeng Li, Haoyang Zou, Ruijie Xu, Run-Ze Fan, Lyumanshan Ye, Ethan Chern, Yixin Ye, Yikai Zhang, Yuqing Yang, Ting Wu, Binjie Wang, Shichao Sun, Yang Xiao, Yiyuan Li, Fan Zhou, Steffi Chern, Yiwei Qin, Yan Ma, Jiadi Su, Yixiu Liu, Yuxiang Zheng, Shaoting Zhang, Dahua Lin, Yu Qiao, Pengfei Liu:
OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI. - David Debot, Pietro Barbiero, Francesco Giannini, Gabriele Ciravegna, Michelangelo Diligenti, Giuseppe Marra:
Interpretable Concept-Based Memory Reasoning. - Yongyuan Liang, Tingqiang Xu, Kaizhe Hu, Guangqi Jiang, Furong Huang, Huazhe Xu:
Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion. - Yuqing Wang, Ye He, Molei Tao:
Evaluating the design space of diffusion-based generative models. - Grzegorz Stefanski, Pawel Daniluk, Artur Szumaczuk, Jakub Tkaczuk:
SOI: Scaling Down Computational Complexity by Estimating Partial States of the Model. - Yunzhe Qi, Yikun Ban, Arindam Banerjee, Jingrui He:
Robust Neural Contextual Bandit against Adversarial Corruptions. - Weimin Bai, Yifei Wang, Wenzheng Chen, He Sun:
An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations. - Lin Chen, Xilin Wei, Jinsong Li, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Zehui Chen, Haodong Duan, Lin Bin, Zhenyu Tang, Li Yuan, Yu Qiao, Dahua Lin, Feng Zhao, Jiaqi Wang:
ShareGPT4Video: Improving Video Understanding and Generation with Better Captions. - Hanna Foerster, Robert Mullins, Ilia Shumailov, Jamie Hayes:
Beyond Slow Signs in High-fidelity Model Extraction. - Aditya Bommakanti, Harshith Reddy Vonteri, Konstantinos Skitsas, Sayan Ranu, Davide Mottin, Panagiotis Karras:
FUGAL: Feature-fortified Unrestricted Graph Alignment. - Anish Madan, Neehar Peri, Shu Kong, Deva Ramanan:
Revisiting Few-Shot Object Detection with Vision-Language Models. - Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi:
Progressive Entropic Optimal Transport Solvers. - Dorian Baudry, Hugo Richard, Maria Cherifa, Vianney Perchet, Clément Calauzènes:
Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits. - Alexander Denker, Francisco Vargas, Shreyas Padhy, Kieran Didi, Simon V. Mathis, Riccardo Barbano, Vincent Dutordoir, Emile Mathieu, Urszula Julia Komorowska, Pietro Lió:
DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform. - Anthony Fuller, Daniel G. Kyrollos, Yousef Yassin, James R. Green:
LookHere: Vision Transformers with Directed Attention Generalize and Extrapolate. - Yan Huang, Xiang Li, Yipeng Shen, Niao He, Jinming Xu:
Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes. - Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael C. Mozer, Sanjeev Arora:
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. - Yonghan Jung, Min Woo Park, Sanghack Lee:
Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference. - Ryoma Yataka, Adriano Cardace, Perry Wang, Petros Boufounos, Ryuhei Takahashi:
RETR: Multi-View Radar Detection Transformer for Indoor Perception. - Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini:
On the Scalability of GNNs for Molecular Graphs. - Yinxuan Huang, Chengmin Gao, Bin Li, Xiangyang Xue:
Improving Viewpoint-Independent Object-Centric Representations through Active Viewpoint Selection. - Yixuan Xu, Hanrui Zhang, Yu Cheng, Vincent Conitzer:
Aggregating Quantitative Relative Judgments: From Social Choice to Ranking Prediction. - Jieyu Zhang, Weikai Huang, Zixian Ma, Oscar Michel, Dong He, Tanmay Gupta, Wei-Chiu Ma, Ali Farhadi, Aniruddha Kembhavi, Ranjay Krishna:
Task Me Anything. - Kai Chen, Yiyao Ma, Xingyu Lin, Stephen James, Jianshu Zhou, Yun-Hui Liu, Pieter Abbeel, Qi Dou:
Vision Foundation Model Enables Generalizable Object Pose Estimation. - Deepak Ravikumar, Efstathia Soufleri, Kaushik Roy:
Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature. - Chen Hang, Zhe Ma, Haoming Chen, Xuwei Fang, Vincent Xie, Faming Fang, Guixu Zhang, Hongbin Wang:
Exploring Fixed Point in Image Editing: Theoretical Support and Convergence Optimization. - Zunnan Xu, Yukang Lin, Haonan Han, Sicheng Yang, Ronghui Li, Yachao Zhang, Xiu Li:
MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models. - Yann Bourreau, Marco Bressan, T.-H. Hubert Chan, Qipeng Kuang, Mauro Sozio:
Efficient Streaming Algorithms for Graphlet Sampling. - Zhenzhi Wang, Yixuan Li, Yanhong Zeng, Youqing Fang, Yuwei Guo, Wenran Liu, Jing Tan, Kai Chen, Tianfan Xue, Bo Dai, Dahua Lin:
HumanVid: Demystifying Training Data for Camera-controllable Human Image Animation. - Eyar Azar, Boaz Nadler:
Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data. - Sunghyeon Woo, Baeseong Park, Byeongwook Kim, Minjung Jo, Se Jung Kwon, Dongsuk Jeon, Dongsoo Lee:
DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation. - Andrew Szot, Bogdan Mazoure, Harsh Agrawal, R. Devon Hjelm, Zsolt Kira, Alexander Toshev:
Grounding Multimodal Large Language Models in Actions. - Adela Frances DePavia, Olga Medrano Martín del Campo, Erasmo Tani:
Optimal Algorithms for Learning Partitions with Faulty Oracles. - Ning Ding, Yehui Tang, Haochen Qin, Zhenli Zhou, Chao Xu, Lin Li, Kai Han, Heng Liao, Yunhe Wang:
MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers. - Zeng Tao, Tong Yang, Junxiong Lin, Xinji Mai, Haoran Wang, Beining Wang, Enyu Zhou, Yan Wang, Wenqiang Zhang:
LCGen: Mining in Low-Certainty Generation for View-consistent Text-to-3D. - Yunwei Ren, Zixuan Wang, Jason D. Lee:
Learning and Transferring Sparse Contextual Bigrams with Linear Transformers. - Bei Li, Tong Zheng, Rui Wang, Jiahao Liu, Qingyan Guo, Junliang Guo, Xu Tan, Tong Xiao, Jingbo Zhu, Jingang Wang, Xunliang Cai:
Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning. - Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora:
Public-data Assisted Private Stochastic Optimization: Power and Limitations. - Xixi Jia, Fangchen Feng, Deyu Meng, Defeng Sun:
Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing. - Zhenxiong Tan, Kaixin Wang, Xinchao Wang:
Implicit Curriculum in Procgen Made Explicit. - Daiqing Qi, Handong Zhao, Sheng Li:
Easy Regional Contrastive Learning of Expressive Fashion Representations. - Guanyu Nie, Vaneet Aggarwal, Christopher J. Quinn:
Gradient Methods for Online DR-Submodular Maximization with Stochastic Long-Term Constraints. - Weiyun Wang, Shuibo Zhang, Yiming Ren, Yuchen Duan, Tiantong Li, Shuo Liu, Mengkang Hu, Zhe Chen, Kaipeng Zhang, Lewei Lu, Xizhou Zhu, Ping Luo, Yu Qiao, Jifeng Dai, Wenqi Shao, Wenhai Wang:
Needle In A Multimodal Haystack. - Artur Szalata, Andrew Benz, Robrecht Cannoodt, Mauricio Cortes, Jason Fong, Sunil Kuppasani, Richard Lieberman, Tianyu Liu, Javier Mas-Rosario, Rico Meinl, Jalil Nourisa, Jared Tumiel, Tin M. Tunjic, Mengbo Wang, Noah Weber, Hongyu Zhao, Benedict Anchang, Fabian J. Theis, Malte Luecken, Daniel Burkhardt:
A benchmark for prediction of transcriptomic responses to chemical perturbations across cell types. - Zhou Fang, Yong-Lu Li, Lixin Yang, Cewu Lu:
General Articulated Objects Manipulation in Real Images via Part-Aware Diffusion Process. - Noah Golowich, Ankur Moitra:
Edit Distance Robust Watermarks via Indexing Pseudorandom Codes. - Kanan Gupta, Jonathan W. Siegel, Stephan Wojtowytsch:
Nesterov acceleration despite very noisy gradients. - Chandramouli Shama Sastry, Sri Harsha Dumpala, Sageev Oore:
DiffAug: A Diffuse-and-Denoise Augmentation for Training Robust Classifiers. - Jiaxi Hu, Yuehong Hu, Wei Chen, Ming Jin, Shirui Pan, Qingsong Wen, Yuxuan Liang:
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective. - Nicolás Astorga, Tennison Liu, Nabeel Seedat, Mihaela van der Schaar:
Active Learning with LLMs for Partially Observed and Cost-Aware Scenarios. - Minghui Chen, Meirui Jiang, Xin Zhang, Qi Dou, Zehua Wang, Xiaoxiao Li:
Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning. - Di Ming, Peng Ren, Yunlong Wang, Xin Feng:
Boosting the Transferability of Adversarial Attack on Vision Transformer with Adaptive Token Tuning. - Zhenwei Tang, Difan Jiao, Reid McIlroy-Young, Jon M. Kleinberg, Siddhartha Sen, Ashton Anderson:
Maia-2: A Unified Model for Human-AI Alignment in Chess. - Yuan Qiu, Nolan Bridges, Peng Chen:
Derivative-enhanced Deep Operator Network. - Shogo Iwazaki, Shinya Suzumura:
No-Regret Bandit Exploration based on Soft Tree Ensemble Model. - Hoin Jung, Taeuk Jang, Xiaoqian Wang:
A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks. - Eleonora Gualdoni, Mycal Tucker, Roger Levy, Noga Zaslavsky:
Bridging semantics and pragmatics in information-theoretic emergent communication. - Tom Sander, Pierre Fernandez, Alain Durmus, Matthijs Douze, Teddy Furon:
Watermarking Makes Language Models Radioactive. - Natalie Maus, Kyurae Kim, David Eriksson, Geoff Pleiss, John P. Cunningham, Jacob R. Gardner:
Approximation-Aware Bayesian Optimization. - Bonwoo Lee, Jeongyoun Ahn, Cheolwoo Park:
Differential Privacy in Scalable General Kernel Learning via $K$-means Nystr{\"o}m Random Features. - Siwei Tu, Weidong Yang, Ben Fei:
Taming Generative Diffusion Prior for Universal Blind Image Restoration. - Taewon Park, Hyun-Chul Kim, Minho Lee:
Discrete Dictionary-based Decomposition Layer for Structured Representation Learning. - Shenghai Yuan, Jinfa Huang, Yongqi Xu, Yaoyang Liu, Shaofeng Zhang, Yujun Shi, Ruijie Zhu, Xinhua Cheng, Jiebo Luo, Li Yuan:
ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation. - Jonas Kulhanek, Songyou Peng, Zuzana Kukelova, Marc Pollefeys, Torsten Sattler:
WildGaussians: 3D Gaussian Splatting In the Wild. - Boxuan Zhang, Jianing Zhu, Zengmao Wang, Tongliang Liu, Bo Du, Bo Han:
What If the Input is Expanded in OOD Detection? - Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec:
RelBench: A Benchmark for Deep Learning on Relational Databases. - Yikun Ban, Jiaru Zou, Zihao Li, Yunzhe Qi, Dongqi Fu, Jian Kang, Hanghang Tong, Jingrui He:
PageRank Bandits for Link Prediction. - Zhiqi Li, Yiming Chen, Peidong Liu:
DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation. - Bin Fan, Jiaoyang Yin, Yuchao Dai, Chao Xu, Tiejun Huang, Boxin Shi:
Spatio-Temporal Interactive Learning for Efficient Image Reconstruction of Spiking Cameras. - Aleksandr V. Lobanov, Alexander V. Gasnikov, Andrey Krasnov:
Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values. - Andreas Schlaginhaufen, Maryam Kamgarpour:
Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning. - Jiahao Wang, Caixia Yan, Haonan Lin, Weizhan Zhang, Mengmeng Wang, Tieliang Gong, Guang Dai, Hao Sun:
OneActor: Consistent Subject Generation via Cluster-Conditioned Guidance. - Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis:
Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models. - Zhengyi Li, Kang Yang, Jin Tan, Wen-jie Lu, Haoqi Wu, Xiao Wang, Yu Yu, Derun Zhao, Yancheng Zheng, Minyi Guo, Jingwen Leng:
Nimbus: Secure and Efficient Two-Party Inference for Transformers. - Misha Khodak, Lester Mackey, Alexandra Chouldechova, Miro Dudík:
SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation. - Rebecca Saul, Chang Liu, Noah Fleischmann, Richard Zak, Kristopher K. Micinski, Edward Raff, James Holt:
Is Function Similarity Over-Engineered? Building a Benchmark. - Levi E. Lingsch, Dana Grund, Siddhartha Mishra, Georgios Kissas:
FUSE: Fast Unified Simulation and Estimation for PDEs. - Dongyan Lucy Huo, Yixuan Zhang, Yudong Chen, Qiaomin Xie:
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize. - Anka Reuel-Lamparth, Amelia F. Hardy, Chandler Smith, Max Lamparth, Malcolm Hardy, Mykel J. Kochenderfer:
BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices. - Joel Dyer, Nicholas Bishop, Yorgos Felekis, Fabio Massimo Zennaro, Anisoara Calinescu, Theodoros Damoulas, Michael J. Wooldridge:
Interventionally Consistent Surrogates for Complex Simulation Models. - Yutao Dou, Huimin Yu, Wei Li, Jingyang Li, Fei Xia, Jian Xiao:
PEACE: A Dataset of Pharmaceutical Care for Cancer Pain Analgesia Evaluation and Medication Decision. - Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao:
Depth Anything V2. - Jacopo Dapueto, Nicoletta Noceti, Francesca Odone:
Transferring disentangled representations: bridging the gap between synthetic and real images. - Zehui Li, Yuhao Ni, Guoxuan Xia, William A. V. Beardall, Akashaditya Das, Guy-Bart Stan, Yiren Zhao:
Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences. - Jikang Cheng, Zhiyuan Yan, Ying Zhang, Yuhao Luo, Zhongyuan Wang, Chen Li:
Can We Leave Deepfake Data Behind in Training Deepfake Detector? - Dongyu Ru, Lin Qiu, Xiangkun Hu, Tianhang Zhang, Peng Shi, Shuaichen Chang, Cheng Jiayang, Cunxiang Wang, Shichao Sun, Huanyu Li, Zizhao Zhang, Binjie Wang, Jiarong Jiang, Tong He, Zhiguo Wang, Pengfei Liu, Yue Zhang, Zheng Zhang:
RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation. - Ted de Vries Lentsch, Holger Caesar, Dariu Gavrila:
UNION: Unsupervised 3D Object Detection using Object Appearance-based Pseudo-Classes. - Wei Jiang, Sifan Yang, Yibo Wang, Lijun Zhang:
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions. - Xinran Li, Ling Pan, Jun Zhang:
Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning. - Kien X. Nguyen, Fengchun Qiao, Arthur Trembanis, Xi Peng:
SeafloorAI: A Large-scale Vision-Language Dataset for Seafloor Geological Survey. - Brandon Huang, Chancharik Mitra, Leonid Karlinsky, Assaf Arbelle, Trevor Darrell, Roei Herzig:
Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning. - Baiyu Su, Qiang Liu:
Quadratic Quantum Variational Monte Carlo. - Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer:
Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics. - Chengsen Wang, Qi Qi, Jingyu Wang, Haifeng Sun, Zirui Zhuang, Jinming Wu, Jianxin Liao:
Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective. - Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun:
Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure. - Eyal Michaeli, Ohad Fried:
Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation. - Tianhang Wang, Fan Lu, Zehan Zheng, Zhijun Li, Guang Chen, Changjun Jiang:
RCDN: Towards Robust Camera-Insensitivity Collaborative Perception via Dynamic Feature-based 3D Neural Modeling. - Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu, Yitao Liang, Jianzhu Ma, James Y. Zou, Stefano Ermon:
TFG: Unified Training-Free Guidance for Diffusion Models. - Junjiao Tian, Chengyue Huang, Zsolt Kira:
Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models. - Xiaoshuai Hao, Mengchuan Wei, Yifan Yang, Haimei Zhao, Hui Zhang, Yi Zhou, Qiang Wang, Weiming Li, Lingdong Kong, Jing Zhang:
Is Your HD Map Constructor Reliable under Sensor Corruptions? - Felipe Maia Polo, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, Mikhail Yurochkin:
Efficient multi-prompt evaluation of LLMs. - Ziyao Wang, Zheyu Shen, Yexiao He, Guoheng Sun, Hongyi Wang, Lingjuan Lyu, Ang Li:
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations. - Nam Phuong Tran, The-Anh Ta, Shuqing Shi, Debmalya Mandal, Yali Du, Long Tran-Thanh:
Learning the Expected Core of Strictly Convex Stochastic Cooperative Games. - Mingzhen Huang, Jialing Cai, Shan Jia, Vishnu Suresh Lokhande, Siwei Lyu:
ParallelEdits: Efficient Multi-Aspect Text-Driven Image Editing with Attention Grouping. - Regev Cohen, Idan Kligvasser, Ehud Rivlin, Daniel Freedman:
Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models. - Christos Thrampoulidis:
Implicit Optimization Bias of Next-token Prediction in Linear Models. - William Redman, Francisco Acosta, Santiago Acosta-Mendoza, Nina Miolane:
Not so griddy: Internal representations of RNNs path integrating more than one agent. - Haiyun Yao, Zongbo Han, Huazhu Fu, Xi Peng, Qinghua Hu, Changqing Zhang:
Out-Of-Distribution Detection with Diversification (Provably). - Wenjia Xie, Hao Wang, Luankang Zhang, Rui Zhou, Defu Lian, Enhong Chen:
Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model. - Huaijin Wu, Xinyu Ye, Junchi Yan:
QVAE-Mole: The Quantum VAE with Spherical Latent Variable Learning for 3-D Molecule Generation. - Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin Jamieson:
Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning. - Qi Lv, Xiang Deng, Gongwei Chen, Michael Yu Wang, Liqiang Nie:
Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL. - Nicholas Rittler, Kamalika Chaudhuri:
Distribution Learning with Valid Outputs Beyond the Worst-Case. - Christopher T. H. Teo, Milad Abdollahzadeh, Xinda Ma, Ngai-Man Cheung:
FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation. - Irene Huang, Wei Lin, Muhammad Jehanzeb Mirza, Jacob A. Hansen, Sivan Doveh, Victor Butoi, Roei Herzig, Assaf Arbelle, Hilde Kuehne, Trevor Darrell, Chuang Gan, Aude Oliva, Rogério Feris, Leonid Karlinsky:
ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs. - Yuhong Li, Yingbing Huang, Bowen Yang, Bharat Venkitesh, Acyr Locatelli, Hanchen Ye, Tianle Cai, Patrick Lewis, Deming Chen:
SnapKV: LLM Knows What You are Looking for Before Generation. - Yujia Zhou, Zheng Liu, Zhicheng Dou:
Boosting the Potential of Large Language Models with an Intelligent Information Assistant. - Alexander Lappe, Anna Bognár, Ghazaleh Ghamkhari Nejad, Albert Mukovskiy, Lucas Martini, Martin A. Giese, Rufin Vogels:
Parallel Backpropagation for Shared-Feature Visualization. - Massimiliano Datres, Gian Paolo Leonardi, Alessio Figalli, David Sutter:
A two-scale Complexity Measure for Deep Learning Models. - Zhishuai Guo, Tianbao Yang:
Communication-Efficient Federated Group Distributionally Robust Optimization. - Kamalika Chaudhuri, Po-Ling Loh, Shourya Pandey, Purnamrita Sarkar:
On Differentially Private U Statistics. - Marco Miani, Lorenzo Beretta, Søren Hauberg:
Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information. - Wei Chow, Juncheng Li, Qifan Yu, Kaihang Pan, Hao Fei, Zhiqi Ge, Shuai Yang, Siliang Tang, Hanwang Zhang, Qianru Sun:
Unified Generative and Discriminative Training for Multi-modal Large Language Models. - Francesco D'Angelo, Maksym Andriushchenko, Aditya Vardhan Varre, Nicolas Flammarion:
Why Do We Need Weight Decay in Modern Deep Learning? - Kai Hu, Weichen Yu, Yining Li, Tianjun Yao, Xiang Li, Wenhe Liu, Lijun Yu, Zhiqiang Shen, Kai Chen, Matt Fredrikson:
Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization. - Aliaksandra Shysheya, Cristiana Diaconu, Federico Bergamin, Paris Perdikaris, José Miguel Hernández-Lobato, Richard E. Turner, Emile Mathieu:
On conditional diffusion models for PDE simulations. - Jonas Ngnawé, Sabyasachi Sahoo, Yann Pequignot, Frédéric Precioso, Christian Gagné:
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers. - Wanghan Xu, Fenghua Ling, Wenlong Zhang, Tao Han, Hao Chen, Wanli Ouyang, Lei Bai:
Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling. - Yunpeng Gong, Zhun Zhong, Yansong Qu, Zhiming Luo, Rongrong Ji, Min Jiang:
Cross-Modality Perturbation Synergy Attack for Person Re-identification. - Yamin Li, Ange Lou, Ziyuan Xu, Shengchao Zhang, Shiyu Wang, Dario J. Englot, Soheil Kolouri, Daniel Moyer, Roza G. Bayrak, Catie Chang:
NeuroBOLT: Resting-state EEG-to-fMRI Synthesis with Multi-dimensional Feature Mapping. - Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng:
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms. - Manuel Dahnert, Angela Dai, Norman Müller, Matthias Nießner:
Coherent 3D Scene Diffusion From a Single RGB Image. - Lingchen Meng, Jianwei Yang, Rui Tian, Xiyang Dai, Zuxuan Wu, Jianfeng Gao, Yu-Gang Jiang:
DeepStack: Deeply Stacking Visual Tokens is Surprisingly Simple and Effective for LMMs. - Zenan Li, Zhi Zhou, Yuan Yao, Xian Zhang, Yufeng Li, Chun Cao, Fan Yang, Xiaoxing Ma:
Neuro-Symbolic Data Generation for Math Reasoning. - Guande He, Kaiwen Zheng, Jianfei Chen, Fan Bao, Jun Zhu:
Consistency Diffusion Bridge Models. - Benjamin Hoover, Duen Horng Chau, Hendrik Strobelt, Parikshit Ram, Dmitry Krotov:
Dense Associative Memory Through the Lens of Random Features. - Jin-Hwi Park, Hae-Gon Jeon:
A Simple yet Universal Framework for Depth Completion. - William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic:
Identifying Equivalent Training Dynamics. - Yingjun Shen, Haizhao Dai, Qihe Chen, Yan Zeng, Jiakai Zhang, Yuan Pei, Jingyi Yu:
DRACO: A Denoising-Reconstruction Autoencoder for Cryo-EM. - Liulei Li, Wenguan Wang, Yi Yang:
Human-Object Interaction Detection Collaborated with Large Relation-driven Diffusion Models. - David Janz, Alexander E. Litvak, Csaba Szepesvári:
Ensemble sampling for linear bandits: small ensembles suffice. - Mohammad-Amin Charusaie, Samira Samadi:
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems. - Shan Chen, Jack Gallifant, Mingye Gao, Pedro Moreira, Nikolaj Munch, Ajay Muthukkumar, Arvind Rajan, Jaya Kolluri, Amelia Fiske, Janna Hastings, Hugo J. W. L. Aerts, Brian Anthony, Leo Anthony Celi, William G. La Cava, Danielle S. Bitterman:
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias. - Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, El Houcine Bergou:
If You Want to Be Robust, Be Wary of Initialization. - Haoqun Cao, Zizhuo Meng, Tianjun Ke, Feng Zhou:
Is Score Matching Suitable for Estimating Point Processes? - Nivasini Ananthakrishnan, Nika Haghtalab, Chara Podimata, Kunhe Yang:
Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions. - Bochuan Cao, Jinyuan Jia, Chuxuan Hu, Wenbo Guo, Zhen Xiang, Jinghui Chen, Bo Li, Dawn Song:
Data Free Backdoor Attacks. - Chenyu Yang, Xizhou Zhu, Jinguo Zhu, Weijie Su, Junjie Wang, Xuan Dong, Wenhai Wang, Lewei Lu, Bin Li, Jie Zhou, Yu Qiao, Jifeng Dai:
Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning. - Zirui Yan, Ali Tajer:
Linear Causal Bandits: Unknown Graph and Soft Interventions. - Chenyang Zhang, Difan Zou, Yuan Cao:
The Implicit Bias of Adam on Separable Data. - Abhimanyu Hans, John Kirchenbauer, Yuxin Wen, Neel Jain, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein:
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs. - Yang Zhou, Zhuoming Chen, Zhaozhuo Xu, Victoria Lin, Beidi Chen:
SIRIUS : Contexual Sparisty with Correction for Efficient LLMs. - Boyuan Chen, Diego Marti Monso, Yilun Du, Max Simchowitz, Russ Tedrake, Vincent Sitzmann:
Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion. - Yuki Minai, Joana Soldado-Magraner, Matthew A. Smith, Byron M. Yu:
MiSO: Optimizing brain stimulation to create neural activity states. - Hanlin Gu, WinKent Ong, Chee Seng Chan, Lixin Fan:
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity. - Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei W. Koh, Bryan Hooi:
Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in LLMs. - Joscha Cüppers, Sascha Xu, Ahmed Musa, Jilles Vreeken:
Causal Discovery from Event Sequences by Local Cause-Effect Attribution. - João Monteiro, Pierre-André Noël, Étienne Marcotte, Sai Rajeswar Mudumba, Valentina Zantedeschi, David Vázquez, Nicolas Chapados, Chris Pal, Perouz Taslakian:
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content. - Haolin Liu, Artin Tajdini, Andrew Wagenmaker, Chen-Yu Wei:
Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification. - Xiaodan Chen, Xiucheng Li, Xinyang Chen, Zhijun Li:
Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics. - Ioar Casado, Luis A. Ortega Andrés, Aritz Pérez, Andrés R. Masegosa:
PAC-Bayes-Chernoff bounds for unbounded losses. - Jacob Dunefsky, Philippe Chlenski, Neel Nanda:
Transcoders find interpretable LLM feature circuits. - Qian Chen, Tianjian Zhang, Linxin Yang, Qingyu Han, Akang Wang, Ruoyu Sun, Xiaodong Luo, Tsung-Hui Chang:
SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization. - Anchit Jain, Rozhin Nobahari, Aristide Baratin, Stefano Sarao Mannelli:
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training. - Shuo Yu, Shan Jin, Ming Li, Tabinda Sarwar, Feng Xia:
Long-range Brain Graph Transformer. - Kai Hu, Jinhao Li, Yuan Zhang, Xiongjun Ye, Xieping Gao:
One-to-Multiple: A Progressive Style Transfer Unsupervised Domain-Adaptive Framework for Kidney Tumor Segmentation. - Tiancheng Wang, Yuguang Yang, Linlin Yang, Shaohui Lin, Juan Zhang, Guodong Guo, Baochang Zhang:
CLIP in Mirror: Disentangling text from visual images through reflection. - Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick, Nadia Polikarpova, Loris D'Antoni:
Grammar-Aligned Decoding. - Chiara Mastrogiuseppe, Rubén Moreno-Bote:
Controlled maximal variability along with reliable performance in recurrent neural networks. - Sangwoong Yoon, Himchan Hwang, Dohyun Kwon, Yung-Kyun Noh, Frank C. Park:
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models. - Naveen Raman, Zheyuan Shi, Fei Fang:
Global Rewards in Restless Multi-Armed Bandits. - Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, David Belius:
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression. - Yang Peng, Liangyu Zhang, Zhihua Zhang:
Statistical Efficiency of Distributional Temporal Difference Learning. - Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis:
Faster Repeated Evasion Attacks in Tree Ensembles. - Jia Syuen Lim, Zhuoxiao Chen, Zhi Chen, Mahsa Baktashmotlagh, Xin Yu, Zi Huang, Yadan Luo:
DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection. - Haoran You, Yipin Guo, Yichao Fu, Wei Zhou, Huihong Shi, Xiaofan Zhang, Souvik Kundu, Amir Yazdanbakhsh, Yingyan (Celine) Lin:
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization. - Yufei Guo, Yuanpei Chen, Zecheng Hao, Weihang Peng, Zhou Jie, Yuhan Zhang, Xiaode Liu, Zhe Ma:
Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks. - Meijun Wang, Yu Meng, Zhongwei Qiu, Chao Zheng, Yan Xu, Pengxiaorui, Jian Gao:
Pedestrian-Centric 3D Pre-collision Pose and Shape Estimation from Dashcam Perspective. - Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Yusuke Kato, Kazuki Kozuka:
Aligning Diffusion Models by Optimizing Human Utility. - Qijun Luo, Hengxu Yu, Xiao Li:
BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models. - Rayen Dhahri, Alexander Immer, Bertrand Charpentier, Stephan Günnemann, Vincent Fortuin:
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood. - Yifan Yang, Zhaofeng Si, Siwei Lyu, Kaiyi Ji:
First-Order Minimax Bilevel Optimization. - Hongyu Cheng, Sammy Khalife, Barbara Fiedorowicz, Amitabh Basu:
Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut. - Haitao Li, You Chen, Qingyao Ai, Yueyue Wu, Ruizhe Zhang, Yiqun Liu:
LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models. - Yang Liu, Chenchen Jing, Hengtao Li, Muzhi Zhu, Hao Chen, Xinlong Wang, Chunhua Shen:
A Simple Image Segmentation Framework via In-Context Examples. - Tianyi Zhou, Deqing Fu, Vatsal Sharan, Robin Jia:
Pre-trained Large Language Models Use Fourier Features to Compute Addition. - Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter:
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators. - Sharmita Dey, Sarath Ravindran Nair:
ReMAP: Neural Model Reprogramming with Network Inversion and Retrieval-Augmented Mapping for Adaptive Motion Forecasting. - Jialong Zuo, Ying Nie, Hanyu Zhou, Huaxin Zhang, Haoyu Wang, Tianyu Guo, Nong Sang, Changxin Gao:
Cross-video Identity Correlating for Person Re-identification Pre-training. - Shuaifeng Li, Mao Ye, Lihua Zhou, Nianxin Li, Siying Xiao, Song Tang, Xiatian Zhu:
Cloud Object Detector Adaptation by Integrating Different Source Knowledge. - Zijian Zhou, Xiaoqiang Lin, Xinyi Xu, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low:
DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning. - Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba:
Mirror and Preconditioned Gradient Descent in Wasserstein Space. - Heewoong Noh, Namkyeong Lee, Gyoung S. Na, Chanyoung Park:
Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge. - Sattar Vakili, Julia Olkhovskaya:
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm. - Zengzhi Wang, Xuefeng Li, Rui Xia, Pengfei Liu:
MathPile: A Billion-Token-Scale Pretraining Corpus for Math. - Gabriel Nobis, Maximilian Springenberg, Marco Aversa, Michael Detzel, Rembert Daems, Roderick Murray-Smith, Shinichi Nakajima, Sebastian Lapuschkin, Stefano Ermon, Tolga Birdal, Manfred Opper, Christoph Knochenhauer, Luis Oala, Wojciech Samek:
Generative Fractional Diffusion Models. - Xinyue Li, Rishi Sonthalia:
Least Squares Regression Can Exhibit Under-Parameterized Double Descent. - Yuhan Zhu, Yuyang Ji, Zhiyu Zhao, Gangshan Wu, Limin Wang:
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation. - Wenjing Yan, Xuanyu Cao:
Decentralized Noncooperative Games with Coupled Decision-Dependent Distributions. - Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon:
Geometric Trajectory Diffusion Models. - Haibin He, Maoyuan Ye, Jing Zhang, Juhua Liu, Bo Du, Dacheng Tao:
GoMatching: A Simple Baseline for Video Text Spotting via Long and Short Term Matching. - Yuheng Shi, Minjing Dong, Chang Xu:
Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model. - Yitao Xu, Tong Zhang, Sabine Süsstrunk:
AdanCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer. - Junfeng Ni, Yixin Chen, Bohan Jing, Nan Jiang, Bin Wang, Bo Dai, Puhao Li, Yixin Zhu, Song-Chun Zhu, Siyuan Huang:
PhyRecon: Physically Plausible Neural Scene Reconstruction. - Mingze Wang, Weinan E:
Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling. - Pankaj K. Agarwal, Sharath Raghvendra, Pouyan Shirzadian, Keegan Yao:
A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem. - Yohann Perron, Vladyslav Sydorov, Adam P. Wijker, Damian Evans, Christophe Pottier, Loïc Landrieu:
Archaeoscape: Bringing Aerial Laser Scanning Archaeology to the Deep Learning Era. - Chenxin Tao, Xizhou Zhu, Shiqian Su, Lewei Lu, Changyao Tian, Xuan Luo, Gao Huang, Hongsheng Li, Yu Qiao, Jie Zhou, Jifeng Dai:
Learning 1D Causal Visual Representation with De-focus Attention Networks. - Leon Lufkin, Andrew M. Saxe, Erin Grant:
Nonlinear dynamics of localization in neural receptive fields. - Vincent Cohen-Addad, Tommaso d'Orsi, Anupam Gupta, Euiwoong Lee, Debmalya Panigrahi:
Learning-Augmented Approximation Algorithms for Maximum Cut and Related Problems. - Shirley Wu, Shiyu Zhao, Qian Huang, Kexin Huang, Michihiro Yasunaga, Kaidi Cao, Vassilis N. Ioannidis, Karthik Subbian, Jure Leskovec, James Y. Zou:
AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning. - Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin M. Solomon:
Score Distillation via Reparametrized DDIM. - Kaiyan Zhang, Sihang Zeng, Ermo Hua, Ning Ding, Zhang-Ren Chen, Zhiyuan Ma, Haoxin Li, Ganqu Cui, Biqing Qi, Xuekai Zhu, Xingtai Lv, Jinfang Hu, Zhiyuan Liu, Bowen Zhou:
UltraMedical: Building Specialized Generalists in Biomedicine. - Riccardo Cadei, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello:
Smoke and Mirrors in Causal Downstream Tasks. - Felix Petersen, Christian Borgelt, Tobias Sutter, Hilde Kuehne, Oliver Deussen, Stefano Ermon:
Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms. - Chandra Sekhar Mukherjee, Nikhil Deorkar, Jiapeng Zhang:
Capturing the denoising effect of PCA via compression ratio. - Mengxi Zhang, Wenhao Wu, Yu Lu, Yuxin Song, Kang Rong, Huanjin Yao, Jianbo Zhao, Fanglong Liu, Haocheng Feng, Jingdong Wang, Yifan Sun:
Automated Multi-level Preference for MLLMs. - Jialu Li, Yu Wang, Pengfei Zhu, Wanyu Lin, Qinghua Hu:
What Matters in Graph Class Incremental Learning? An Information Preservation Perspective. - Andrew M. Bean, Simi Hellsten, Harry Mayne, Jabez Magomere, Ethan Chi, Ryan Chi, Scott Hale, Hannah Rose Kirk:
LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low Resource and Extinct Languages. - Jiacheng Cen, Anyi Li, Ning Lin, Yuxiang Ren, Zihe Wang, Wenbing Huang:
Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks? - Yiyang Sun, Tong Wang, Cynthia Rudin:
Improving Decision Sparsity. - Qiufeng Wang, Xu Yang, Fu Feng, Jing Wang, Xin Geng:
Cluster-Learngene: Inheriting Adaptive Clusters for Vision Transformers. - Wei Tang, Yin-Fang Yang, Zhaofei Wang, Weijia Zhang, Min-Ling Zhang:
Multi-Instance Partial-Label Learning with Margin Adjustment. - Dinh Duc Cao, Seok Joon Kim, Kyusung Cho:
Geometric Exploitation for Indoor Panoramic Semantic Segmentation. - Zhehao Huang, Xinwen Cheng, JingHao Zheng, Haoran Wang, Zhengbao He, Tao Li, Xiaolin Huang:
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement. - Chenqing Hua, Bozitao Zhong, Sitao Luan, Liang Hong, Guy Wolf, Doina Precup, Shuangjia Zheng:
ReactZyme: A Benchmark for Enzyme-Reaction Prediction. - Kimon Protopapas, Anas Barakat:
Policy Mirror Descent with Lookahead. - Andreas Maurer:
Generalization of Hamiltonian algorithms. - Xuxing Chen, Abhishek Roy, Yifan Hu, Krishnakumar Balasubramanian:
Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data. - Shervin Khalafi, Dongsheng Ding, Alejandro Ribeiro:
Constrained Diffusion Models via Dual Training. - David Holzmüller, Léo Grinsztajn, Ingo Steinwart:
Better by default: Strong pre-tuned MLPs and boosted trees on tabular data. - Chuanyang Zheng, Yihang Gao, Han Shi, Minbin Huang, Jingyao Li, Jing Xiong, Xiaozhe Ren, Michael K. Ng, Xin Jiang, Zhenguo Li, Yu Li:
DAPE: Data-Adaptive Positional Encoding for Length Extrapolation. - Qidong Liu, Xian Wu, Yejing Wang, Zijian Zhang, Feng Tian, Yefeng Zheng, Xiangyu Zhao:
LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation. - Victor Boone, Zihan Zhang:
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs. - Anton Rodomanov, Xiaowen Jiang, Sebastian U. Stich:
Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction. - Xuan Chen, Yuzhou Nie, Wenbo Guo, Xiangyu Zhang:
When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search. - Ying Yang, De Cheng, Chaowei Fang, Yubiao Wang, Changzhe Jiao, Lechao Cheng, Nannan Wang, Xinbo Gao:
Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection. - Kushagra Pandey, Ruihan Yang, Stephan Mandt:
Fast samplers for Inverse Problems in Iterative Refinement models. - Changze Lv, Dongqi Han, Yansen Wang, Xiaoqing Zheng, Xuanjing Huang, Dongsheng Li:
Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators. - Keyon Vafa, Justin Y. Chen, Ashesh Rambachan, Jon M. Kleinberg, Sendhil Mullainathan:
Evaluating the World Model Implicit in a Generative Model. - Yichun Hu, Nathan Kallus, Xiaojie Mao, Yanchen Wu:
Contextual Linear Optimization with Bandit Feedback. - Tomoya Sakai, Haoxiang Qiu, Takayuki Katsuki, Daiki Kimura, Takayuki Osogami, Tadanobu Inoue:
A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation. - Yuwei Zhang, Tong Xia, Jing Han, Yu Wu, Georgios Rizos, Yang Liu, Mohammed Mosuily, Jagmohan Chauhan, Cecilia Mascolo:
Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking. - Lin Chen, Jinsong Li, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Zehui Chen, Haodong Duan, Jiaqi Wang, Yu Qiao, Dahua Lin, Feng Zhao:
Are We on the Right Way for Evaluating Large Vision-Language Models? - Pratiksha Thaker, Amrith Setlur, Steven Z. Wu, Virginia Smith:
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift. - Jake Cunningham, Giorgio Giannone, Mingtian Zhang, Marc Peter Deisenroth:
Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling. - Tiago da Silva, Daniel Augusto de Souza, Diego Mesquita:
Streaming Bayes GFlowNets. - The Viet Bui, Tien Anh Mai, Thanh Hong Nguyen:
Inverse Factorized Soft Q-Learning for Cooperative Multi-agent Imitation Learning. - Zhiqiang Chen, Guofan Fan, Jinying Gao, Lei Ma, Bo Lei, Tiejun Huang, Shan Yu:
Learning from Pattern Completion: Self-supervised Controllable Generation. - Minjie Wang, Quan Gan, David Wipf, Zheng Zhang, Christos Faloutsos, Weinan Zhang, Muhan Zhang, Zhenkun Cai, Jiahang Li, Zunyao Mao, Yakun Song, Jianheng Tang, Yanlin Zhang, Guang Yang, Chuan Lei, Xiao Qin, Ning Li, Han Zhang, Yanbo Wang, Zizhao Zhang:
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs. - Mathieu Carrière, Marc Theveneau, Théo Lacombe:
Diffeomorphic interpolation for efficient persistence-based topological optimization. - Tom Yan, Zachary C. Lipton:
A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning. - Siyi Chen, Huijie Zhang, Minzhe Guo, Yifu Lu, Peng Wang, Qing Qu:
Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing. - Peng Sun, Yi Jiang, Tao Lin:
Efficiency for Free: Ideal Data Are Transportable Representations. - Haoran Luo, Haihong E, Yuhao Yang, Tianyu Yao, Yikai Guo, Zichen Tang, Wentai Zhang, Shiyao Peng, Kaiyang Wan, Meina Song, Wei Lin, Yifan Zhu, Anh Tuan Luu:
Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction. - Jiangwei Weng, Zhiqiang Yan, Ying Tai, Jianjun Qian, Jian Yang, Jun Li:
MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Space. - Yuxin Chen, Junfei Tan, An Zhang, Zhengyi Yang, Leheng Sheng, Enzhi Zhang, Xiang Wang, Tat-Seng Chua:
On Softmax Direct Preference Optimization for Recommendation. - Ben Norman, Jeff Clune:
First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs. - Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron C. Courville, Sai Rajeswar Mudumba:
GenRL: Multimodal-foundation world models for generalization in embodied agents. - Letian Peng, Jingbo Shang:
Quantifying and Optimizing Global Faithfulness in Persona-driven Role-playing. - Amirhosein Ghasemabadi, Muhammad Kamran Janjua, Mohammad Salameh, Di Niu:
Learning Truncated Causal History Model for Video Restoration. - Shady Abu-Hussein, Raja Giryes:
UDPM: Upsampling Diffusion Probabilistic Models. - Weichao Zhou, Wenchao Li:
Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment. - Guoxin Chen, Minpeng Liao, Chengxi Li, Kai Fan:
AlphaMath Almost Zero: Process Supervision without Process. - Ben Adcock, Nick C. Dexter, Sebastian Moraga Scheuermann:
Optimal deep learning of holomorphic operators between Banach spaces. - Jingwu Tang, Gokul Swamy, Fei Fang, Zhiwei Steven Wu:
Multi-Agent Imitation Learning: Value is Easy, Regret is Hard. - Thibault Simonetto, Salah Ghamizi, Maxime Cordy:
Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data. - Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Colin Sandon, Omid Saremi:
How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad. - Dong Jing, Xiaolong He, Yutian Luo, Nanyi Fei, Guoxing Yang, Wei Wei, Huiwen Zhao, Zhiwu Lu:
FineCLIP: Self-distilled Region-based CLIP for Better Fine-grained Understanding. - Richard Nock, Mathieu Guillame-Bert:
Generative Forests. - Haochuan Xu, Ninh Pham:
Scalable DBSCAN with Random Projections. - Qihao Zhou, Haishan Ye, Luo Luo:
Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity. - Mingshuang Luo, Ruibing Hou, Zhuo Li, Hong Chang, Zimo Liu, Yaowei Wang, Shiguang Shan:
M$^3$GPT: An Advanced Multimodal, Multitask Framework for Motion Comprehension and Generation. - Haoran Zhang, Junkai Deng, Xuhui Chen, Fei Hou, Wencheng Wang, Hong Qin, Chen Qian, Ying He:
From Transparent to Opaque: Rethinking Neural Implicit Surfaces with $\alpha$-NeuS. - Stefan Pranger, Hana Chockler, Martin Tappler, Bettina Könighofer:
Test Where Decisions Matter: Importance-driven Testing for Deep Reinforcement Learning. - Rohan Choudhury, Guanglei Zhu, Sihan Liu, Koichiro Niinuma, Kris Kitani, László A. Jeni:
Don't Look Twice: Faster Video Transformers with Run-Length Tokenization. - Pihe Hu, Shaolong Li, Zhuoran Li, Ling Pan, Longbo Huang:
Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training. - Hanxiao Zhang, Lin Ju, Chan Wu, Jinjing Huang, Youshao Xiao, Zhenglei Zhou, Zhiming Fan, Zhaoxin Huan, Siyuan Li, Fanzhuang Meng, Lei Liang, Xiaolu Zhang, Jun Zhou:
Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models. - Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu:
GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations. - Shihao Tu, Linfeng Cao, Daoze Zhang, Junru Chen, Lvbin Ma, Yin Zhang, Yang Yang:
DMNet: Self-comparison Driven Model for Subject-independent Seizure Detection. - Junke Wang, Yi Jiang, Zehuan Yuan, Bingyue Peng, Zuxuan Wu, Yu-Gang Jiang:
OmniTokenizer: A Joint Image-Video Tokenizer for Visual Generation. - Keyi Kong, Xilie Xu, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli:
Perplexity-aware Correction for Robust Alignment with Noisy Preferences. - Derek Lim, Theo Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka:
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof. - Chendi Qian, Andrei Manolache, Christopher Morris, Mathias Niepert:
Probabilistic Graph Rewiring via Virtual Nodes. - Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu-ming Cheung, Amelie Chi Zhou, Bo Han, Xiaowen Chu:
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion. - Shaoteng Liu, Haoqi Yuan, Minda Hu, Yanwei Li, Yukang Chen, Shu Liu, Zongqing Lu, Jiaya Jia:
RL-GPT: Integrating Reinforcement Learning and Code-as-policy. - Xiaolei Liu, Shaoshuai Li, Kaixin Gao, Binfeng Wang:
A Layer-Wise Natural Gradient Optimizer for Training Deep Neural Networks. - Bingqiao Luo, Zhen Zhang, Qian Wang, Bingsheng He:
Multi-Chain Graphs of Graphs: A New Approach to Analyzing Blockchain Datasets. - Mingcheng Li, Dingkang Yang, Yang Liu, Shunli Wang, Jiawei Chen, Shuaibing Wang, Jinjie Wei, Yue Jiang, Qingyao Xu, Xiaolu Hou, Mingyang Sun, Ziyun Qian, Dongliang Kou, Lihua Zhang:
Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning. - Leo Zhou, Joao Basso, Song Mei:
Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm. - Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber, Christopher Potts, Christopher D. Manning:
MoEUT: Mixture-of-Experts Universal Transformers. - Feipeng Ma, Hongwei Xue, Yizhou Zhou, Guangting Wang, Fengyun Rao, Shilin Yan, Yueyi Zhang, Siying Wu, Mike Zheng Shou, Xiaoyan Sun:
Visual Perception by Large Language Model's Weights. - Yongxin Zhu, Bocheng Li, Hang Zhang, Xin Li, Linli Xu, Lidong Bing:
Stabilize the Latent Space for Image Autoregressive Modeling: A Unified Perspective. - Jr-Jen Chen, Yu-Chien Liao, Hsi-Che Lin, Yu-Chu Yu, Yen-Chun Chen, Yu-Chiang Frank Wang:
ReXTime: A Benchmark Suite for Reasoning-Across-Time in Videos. - Donato Crisostomi, Marco Fumero, Daniele Baieri, Florian Bernard, Emanuele Rodolà:
$C^2M^3$: Cycle-Consistent Multi-Model Merging. - Daniel Dauner, Marcel Hallgarten, Tianyu Li, Xinshuo Weng, Zhiyu Huang, Zetong Yang, Hongyang Li, Igor Gilitschenski, Boris Ivanovic, Marco Pavone, Andreas Geiger, Kashyap Chitta:
NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking. - Yuhang Li, Changsheng Li, Ruilin Lv, Rongqing Li, Ye Yuan, Guoren Wang:
LaKD: Length-agnostic Knowledge Distillation for Trajectory Prediction with Any Length Observations. - Byoungwoo Park, Jungwon Choi, Sungbin Lim, Juho Lee:
Stochastic Optimal Control for Diffusion Bridges in Function Spaces. - Ziyang Xiao, Dongxiang Zhang, Xiongwei Han, Xiaojin Fu, Wing Yin Yu, Tao Zhong, Sai Wu, Yuan Wang, Jianwei Yin, Gang Chen:
Enhancing LLM Reasoning via Vision-Augmented Prompting. - Jihyung Kil, Zheda Mai, Justin Lee, Arpita Chowdhury, Zihe Wang, Kerrie Cheng, Lemeng Wang, Ye Liu, Wei-Lun Chao:
MLLM-CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs. - Haoning Wu, Dongxu Li, Bei Chen, Junnan Li:
LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding. - Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, Jonathan Ilgen, Emma Pierson, Pang Wei W. Koh, Yulia Tsvetkov:
MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning. - Qi Song, Tianxiang Gong, Shiqi Gao, Haoyi Zhou, Jianxin Li:
QUEST: Quadruple Multimodal Contrastive Learning with Constraints and Self-Penalization. - Swapnil Bhosale, Haosen Yang, Diptesh Kanojia, Jiankang Deng, Xiatian Zhu:
AV-GS: Learning Material and Geometry Aware Priors for Novel View Acoustic Synthesis. - Andrew Estornell, Yang Liu:
Multi-LLM Debate: Framework, Principals, and Interventions. - Rachel S. Y. Teo, Tan Nguyen:
MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts. - Wenfang Yao, Chen Liu, Kejing Yin, William Kwok-Wai Cheung, Jing Qin:
Addressing Asynchronicity in Clinical Multimodal Fusion via Individualized Chest X-ray Generation. - Zhenghao Lin, Zhibin Gou, Yeyun Gong, Xiao Liu, Yelong Shen, Ruochen Xu, Chen Lin, Yujiu Yang, Jian Jiao, Nan Duan, Weizhu Chen:
Not All Tokens Are What You Need for Pretraining. - Yunpeng Qing, Shunyu Liu, Jingyuan Cong, Kaixuan Chen, Yihe Zhou, Mingli Song:
A2PO: Towards Effective Offline Reinforcement Learning from an Advantage-aware Perspective. - Alex Stergiou:
LAVIB: A Large-scale Video Interpolation Benchmark. - Kaya Stechly, Karthik Valmeekam, Subbarao Kambhampati:
Chain of Thoughtlessness? An Analysis of CoT in Planning. - Xuehao Cui, Guangyang Wu, Zhenghao Gan, Guangtao Zhai, Xiaohong Liu:
Face2QR: A Unified Framework for Aesthetic, Face-Preserving, and Scannable QR Code Generation. - Archit Sharma, Sedrick Scott Keh, Eric Mitchell, Chelsea Finn, Kushal Arora, Thomas Kollar:
A Critical Evaluation of AI Feedback for Aligning Large Language Models. - Wenzhuo Liu, Fei Zhu, Shijie Ma, Cheng-Lin Liu:
MSPE: Multi-Scale Patch Embedding Prompts Vision Transformers to Any Resolution. - Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan:
Global Convergence in Training Large-Scale Transformers. - Luiz F. O. Chamon, Mohammad Reza Karimi Jaghargh, Anna Korba:
Constrained Sampling with Primal-Dual Langevin Monte Carlo. - Duo Zhou, Christopher Brix, Grani A. Hanasusanto, Huan Zhang:
Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes. - Jie Zhu, Yixiong Chen, Mingyu Ding, Ping Luo, Leye Wang, Jingdong Wang:
MoLE: Enhancing Human-centric Text-to-image Diffusion via Mixture of Low-rank Experts. - Zhiyuan Yan, Taiping Yao, Shen Chen, Yandan Zhao, Xinghe Fu, Junwei Zhu, Donghao Luo, Chengjie Wang, Shouhong Ding, Yunsheng Wu, Li Yuan:
DF40: Toward Next-Generation Deepfake Detection. - Jinlin Lai, Justin Domke, Daniel R. Sheldon:
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models. - Tianjiao Luo, Tim Pearce, Huayu Chen, Jianfei Chen, Jun Zhu:
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory. - Ye Tian, Ling Yang, Haotian Yang, Yuan Gao, Yufan Deng, Xintao Wang, Zhaochen Yu, Xin Tao, Pengfei Wan, Di Zhang, Bin Cui:
VideoTetris: Towards Compositional Text-to-Video Generation. - Peter Mørch Groth, Mads Herbert Kerrn, Lars Olsen, Jesper Salomon, Wouter Boomsma:
Kermut: Composite kernel regression for protein variant effects. - Yuchen Hu, Chen Chen, Chao-Han Yang, Chengwei Qin, Pin-Yu Chen, Engsiong Chng, Chao Zhang:
Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech Foundation Models. - Barakeel Fanseu Kamhoua, Huamin Qu:
HOPE: Shape Matching Via Aligning Different K-hop Neighbourhoods. - Jiying Zhang, Zijing Liu, Yu Wang, Bin Feng, Yu Li:
SubgDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning. - Kaushik Sinha:
Non-parametric classification via expand-and-sparsify representation. - Xiaohang Tang, Afonso Marques, Parameswaran Kamalaruban, Ilija Bogunovic:
Adversarially Robust Decision Transformer. - Zichuan Liu, Zefan Wang, Linjie Xu, Jinyu Wang, Lei Song, Tianchun Wang, Chunlin Chen, Wei Cheng, Jiang Bian:
Protecting Your LLMs with Information Bottleneck. - Boxiao Pan, Zhan Xu, Chun-Hao Paul Huang, Krishna Kumar Singh, Yang Zhou, Leonidas J. Guibas, Jimei Yang:
ActAnywhere: Subject-Aware Video Background Generation. - Yerram Varun, Rahul Madhavan, Sravanti Addepalli, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain:
Time-Reversal Provides Unsupervised Feedback to LLMs. - Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans:
UQE: A Query Engine for Unstructured Databases. - Ruihan Gao, Kangle Deng, Gengshan Yang, Wenzhen Yuan, Jun-Yan Zhu:
Tactile DreamFusion: Exploiting Tactile Sensing for 3D Generation. - Nachiket Kotalwar, Alkis Gotovos, Adish Singla:
Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation. - Chaeyun Jang, Hyungi Lee, Jungtaek Kim, Juho Lee:
Model Fusion through Bayesian Optimization in Language Model Fine-Tuning. - Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa:
Mind the Graph When Balancing Data for Fairness or Robustness. - Xinke Jiang, Rihong Qiu, Yongxin Xu, Wentao Zhang, Yichen Zhu, Ruizhe Zhang, Yuchen Fang, Chu Xu, Junfeng Zhao, Yasha Wang:
RAGraph: A General Retrieval-Augmented Graph Learning Framework. - Chenghao Fan, Zhenyi Lu, Wei Wei, Jie Tian, Xiaoye Qu, Dangyang Chen, Yu Cheng:
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion. - Narine Kokhlikyan, Bargav Jayaraman, Florian Bordes, Chuan Guo, Kamalika Chaudhuri:
Measuring Dejavu Memorization Efficiently. - Tehila Dahan, Kfir Y. Levy:
Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML. - Theodore Tsesmelis, Luca Palmieri, Marina Khoroshiltseva, Adeela Islam, Gur Elkin, Ofir Itzhak Shahar, Gianluca Scarpellini, Stefano Fiorini, Yaniv Ohayon, Nadav Alali, Sinem Aslan, Pietro Morerio, Sebastiano Vascon, Elena Gravina, Maria Cristina Napolitano, Giuseppe Scarpati, Gabriel Zuchtriegel, Alexandra Spühler, Michel E. Fuchs, Stuart James, Ohad Ben-Shahar, Marcello Pelillo, Alessio Del Bue:
Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving. - Frederik Kunstner, Alan Milligan, Robin Yadav, Mark Schmidt, Alberto Bietti:
Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models. - Franziska Heeg, Ingo Scholtes:
Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs. - Yang Li, Jinpei Guo, Runzhong Wang, Hongyuan Zha, Junchi Yan:
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization. - Hai-Vy Nguyen, Fabrice Gamboa, Reda Chhaibi, Sixin Zhang, Serge Gratton, Thierry Giaccone:
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification. - Andrea Wynn, Ilia Sucholutsky, Tom Griffiths:
Learning Human-like Representations to Enable Learning Human Values. - Jin-Hong Du, Pratik Patil:
Implicit Regularization Paths of Weighted Neural Representations. - Min Zhao, Hongzhou Zhu, Chendong Xiang, Kaiwen Zheng, Chongxuan Li, Jun Zhu:
Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model. - Eunji Hong, Minh Hieu Nguyen, Mikaela Angelina Uy, Minhyuk Sung:
MV2Cyl: Reconstructing 3D Extrusion Cylinders from Multi-View Images. - Kwangho Kim, Jisu Kim, Larry A. Wasserman, Edward H. Kennedy:
Hierarchical and Density-based Causal Clustering. - Qisen Wang, Yifan Zhao, Jiawei Ma, Jia Li:
How to Use Diffusion Priors under Sparse Views? - Dar Gilboa, Hagay Michaeli, Daniel Soudry, Jarrod R. McClean:
Exponential Quantum Communication Advantage in Distributed Inference and Learning. - Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel:
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits. - Ido Sobol, Chenfeng Xu, Or Litany:
Zero-to-Hero: Enhancing Zero-Shot Novel View Synthesis via Attention Map Filtering. - Kendong Liu, Zhiyu Zhu, Chuanhao Li, Hui Liu, Huanqiang Zeng, Junhui Hou:
PrefPaint: Aligning Image Inpainting Diffusion Model with Human Preference. - Bikang Pan, Wei Huang, Ye Shi:
Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method. - Minyang Tian, Luyu Gao, Shizhuo Dylan Zhang, Xinan Chen, Cunwei Fan, Xuefei Guo, Roland Haas, Pan Ji, Kittithat Krongchon, Yao Li, Shengyan Liu, Di Luo, Yutao Ma, Hao Tong, Kha Trinh, Chenyu Tian, Zihan Wang, Bohao Wu, Shengzhu Yin, Minhui Zhu, Kilian Lieret, Yanxin Lu, Genglin Liu, Yufeng Du, Tianhua Tao, Ofir Press, Jamie Callan, Eliu A. Huerta, Hao Peng:
SciCode: A Research Coding Benchmark Curated by Scientists. - Zheng Chen, Haotong Qin, Yong Guo, Xiongfei Su, Xin Yuan, Linghe Kong, Yulun Zhang:
Binarized Diffusion Model for Image Super-Resolution. - Alejandro Lozano, Jeffrey J. Nirschl, James Burgess, Sanket Rajan Gupte, Yuhui Zhang, Alyssa Unell, Serena Yeung:
Micro-Bench: A Microscopy Benchmark for Vision-Language Understanding. - Zhengkai Lin, Zhihang Fu, Kai Liu, Liang Xie, Binbin Lin, Wenxiao Wang, Deng Cai, Yue Wu, Jieping Ye:
Delving into the Reversal Curse: How Far Can Large Language Models Generalize? - Xueyi Zhang, Mingrui Lao, Peng Zhao, Jun Tang, Yanming Guo, Siqi Cai, Xianghu Yue, Haizhou Li:
Language Without Borders: A Dataset and Benchmark for Code-Switching Lip Reading. - Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang:
On the Parameter Identifiability of Partially Observed Linear Causal Models. - Chau Tran, Duy M. H. Nguyen, Manh-Duy Nguyen, TrungTin Nguyen, Ngan Le, Pengtao Xie, Daniel Sonntag, James Y. Zou, Binh Nguyen, Mathias Niepert:
Accelerating Transformers with Spectrum-Preserving Token Merging. - Guilherme Penedo, Hynek Kydlícek, Loubna Ben Allal, Anton Lozhkov, Margaret Mitchell, Colin A. Raffel, Leandro von Werra, Thomas Wolf:
The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale. - Qi Li, Xiang Liu, Zhenheng Tang, Peijie Dong, Zeyu Li, Xinglin Pan, Xiaowen Chu:
Should We Really Edit Language Models? On the Evaluation of Edited Language Models. - Stefan Stojanovic, Yassir Jedra, Alexandre Proutière:
Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation. - Xin Xiao, Bohong Wu, Jiacong Wang, Chunyuan Li, Xun Zhou, Haoyuan Guo:
Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment. - Oswin So, Cheng Ge, Chuchu Fan:
Solving Minimum-Cost Reach Avoid using Reinforcement Learning. - Dongjoon Lee, Hyeryn Park, Changhee Lee:
Toward a Well-Calibrated Discrimination via Survival Outcome-Aware Contrastive Learning. - Luting Wang, Yang Zhao, Zijian Zhang, Jiashi Feng, Si Liu, Bingyi Kang:
Image Understanding Makes for A Good Tokenizer for Image Generation. - Hideaki Kim:
Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions. - Bowen Ping, Shuo Wang, Hanqing Wang, Xu Han, Yuzhuang Xu, Yukun Yan, Yun Chen, Baobao Chang, Zhiyuan Liu, Maosong Sun:
Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models. - Xilin He, Jingyu Hu, Qinliang Lin, Cheng Luo, Weicheng Xie, Siyang Song, Muhammad Haris Khan, Linlin Shen:
Towards Combating Frequency Simplicity-biased Learning for Domain Generalization. - Lili Wei, Congyan Lang, Ziyi Chen, Tao Wang, Yidong Li, Jun Liu:
Generated and Pseudo Content guided Prototype Refinement for Few-shot Point Cloud Segmentation. - Haoran He, Chenjia Bai, Ling Pan, Weinan Zhang, Bin Zhao, Xuelong Li:
Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training. - Andrew Jesson, Nicolas Beltran-Velez, Quentin Chu, Sweta Karlekar, Jannik Kossen, Yarin Gal, John P. Cunningham, David M. Blei:
Estimating the Hallucination Rate of Generative AI. - Vivian Y. Nastl, Moritz Hardt:
Do causal predictors generalize better to new domains? - Jonathan Wenger, Kaiwen Wu, Philipp Hennig, Jacob R. Gardner, Geoff Pleiss, John P. Cunningham:
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference. - Weiwei Ye, Songgaojun Deng, Qiaosha Zou, Ning Gui:
Frequency Adaptive Normalization For Non-stationary Time Series Forecasting. - Giovanni De Toni, Nastaran Okati, Suhas Thejaswi, Eleni Straitouri, Manuel Gomez Rodriguez:
Towards Human-AI Complementarity with Prediction Sets. - Erik Jenner, Shreyas Kapur, Vasil Georgiev, Cameron Allen, Scott Emmons, Stuart J. Russell:
Evidence of Learned Look-Ahead in a Chess-Playing Neural Network. - Wenhao Yang, Yibo Wang, Peng Zhao, Lijun Zhang:
Universal Online Convex Optimization with 1 Projection per Round. - Maor Ashkenazi, Eran Treister:
Towards Croppable Implicit Neural Representations. - Jinhee Kim, Taesung Kim, Jaegul Choo:
EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models. - Suzanne Duncan, Gianna Leoni, Lee Steven, Keoni Mahelona, Peter-Lucas Jones:
Fit for our purpose, not yours: Benchmark for a low-resource, Indigenous language. - Jerry Yao-Chieh Hu, Weimin Wu, Zhuoru Li, Sophia Pi, Zhao Song, Han Liu:
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs). - Zhixiang Shen, Shuo Wang, Zhao Kang:
Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning. - Andrew Wagenmaker, Lu Mi, Marton Rozsa, Matthew S. Bull, Karel Svoboda, Kayvon Daie, Matthew D. Golub, Kevin Jamieson:
Active learning of neural population dynamics using two-photon holographic optogenetics. - Sheng Yan, Cunhang Fan, Hongyu Zhang, Xiaoke Yang, Jianhua Tao, Zhao Lv:
DARNet: Dual Attention Refinement Network with Spatiotemporal Construction for Auditory Attention Detection. - Yiling Xie, Xiaoming Huo:
High-dimensional (Group) Adversarial Training in Linear Regression. - Yuefei Lyu, Chaozhuo Li, Sihong Xie, Xi Zhang:
Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning. - Arlind Kadra, Sebastian Pineda-Arango, Josif Grabocka:
Interpretable Mesomorphic Networks for Tabular Data. - Aviv Bick, Kevin Y. Li, Eric P. Xing, J. Zico Kolter, Albert Gu:
Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. - Muhammad Umair Nasir, Steven James, Julian Togelius:
GameTraversalBenchmark: Evaluating Planning Abilities Of Large Language Models Through Traversing 2D Game Maps. - Yi-Kai Zhang, Shiyin Lu, Yang Li, Yanqing Ma, Qingguo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, De-Chuan Zhan, Han-Jia Ye:
Wings: Learning Multimodal LLMs without Text-only Forgetting. - Rahul Saxena, Taeyoun Kim, Aman Mehra, Christina Baek, J. Zico Kolter, Aditi Raghunathan:
Predicting the Performance of Foundation Models via Agreement-on-the-Line. - Christian Holberg, Cristopher Salvi:
Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals. - Philipp Schleich, Marta Skreta, Lasse Bjørn Kristensen, Rodrigo A. Vargas-Hernández, Alán Aspuru-Guzik:
Quantum Deep Equilibrium Models. - Xinyi Yu, Haonan Jiang, Li Zhang, Lin Yuanbo Wu, Linlin Ou, Liu Liu:
EfficientCAPER: An End-to-End Framework for Fast and Robust Category-Level Articulated Object Pose Estimation. - Tong Wu, Yinghao Xu, Ryan Po, Mengchen Zhang, Guandao Yang, Jiaqi Wang, Ziwei Liu, Dahua Lin, Gordon Wetzstein:
FiVA: Fine-grained Visual Attribute Dataset for Text-to-Image Diffusion Models. - Jialiang Wang, Xiong Zhou, Deming Zhai, Junjun Jiang, Xiangyang Ji, Xianming Liu:
$\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise. - Sihan Liu, Christopher Ye:
Replicable Uniformity Testing. - Ye Liu, Zongyang Ma, Zhongang Qi, Yang Wu, Ying Shan, Chang Wen Chen:
E.T. Bench: Towards Open-Ended Event-Level Video-Language Understanding. - Ce Zhang, Simon Stepputtis, Katia P. Sycara, Yaqi Xie:
Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models.