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ORCIDEric P. Xing
Eric Poe Xing
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- affiliation: Carnegie Mellon University, School of Computer Science, Pittsburgh, PA, USA
- affiliation: Petuum Inc., Pittsburgh, PA, USA
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2020 – today
- 2026
[i299]David L. Donoho, Jian Kang, Xihong Lin, Bhramar Mukherjee, Dan Nettleton, Rebecca Nugent, Abel Rodriguez, Eric P. Xing, Tian Zheng, Hongtu Zhu:
"Rebuilding" Statistics in the Age of AI: A Town Hall Discussion on Culture, Infrastructure, and Training. CoRR abs/2601.17510 (2026)- [i298]Zhen Wang, Fan Bai, Zhongyan Luo, Jinyan Su, Kaiser Sun, Xinle Yu, Jieyuan Liu, Kun Zhou, Claire Cardie, Mark Dredze, Eric P. Xing, Zhiting Hu:
FIRE-Bench: Evaluating Agents on the Rediscovery of Scientific Insights. CoRR abs/2602.02905 (2026) - 2025
- [j81]Reza Shahriari
, Yichi Yang, Danish Nisar Ahmed Tamboli, Michael Francis Perez, Yuheng Zha, Jinyu Hou, Mingkai Deng, Eric D. Ragan, Jaime Ruiz, Daisy Zhe Wang, Zhiting Hu, Eric P. Xing:
MuCHEx: A Multimodal Conversational Debugging Tool for Interactive Visual Exploration of Hierarchical Object Classification. IEEE Computer Graphics and Applications 45(6): 76-88 (2025) - [c395]Jianshu She, Wenhao Zheng, Zhengzhong Liu, Hongyi Wang, Eric P. Xing, Huaxiu Yao, Qirong Ho:
Token Level Routing Inference System for Edge Devices. ACL (3) 2025: 159-166 - [c394]Guokan Shang, Hadi Abdine, Yousef Khoubrane, Amr Mohamed, Yassine Abbahaddou, Sofiane Ennadir, Imane Momayiz, Xuguang Ren, Eric Moulines, Preslav Nakov, Michalis Vazirgiannis, Eric P. Xing:
Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect. COLING Workshops 2025: 9-30 - [c393]Shehan Munasinghe, Hanan Gani, Wenqi Zhu, Jiale Cao, Eric P. Xing, Fahad Shahbaz Khan, Salman H. Khan:
VideoGLaMM : A Large Multimodal Model for Pixel-Level Visual Grounding in Videos. CVPR 2025: 19036-19046 - [c392]Shaoan Xie, Lingjing, Yujia Zheng, Yu Yao, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang:
SmartCLIP: Modular Vision-language Alignment with Identification Guarantees. CVPR 2025: 29780-29790 - [c391]Jianshu She, Xinyue Li, Eric P. Xing, Zhengzhong Liu, Qirong Ho:
Linear Steerability in Language Models: When It Emerges and How It Evolves. EMNLP (Findings) 2025: 17821-17846 - [c390]Yonghao Zhuang, Lanxiang Hu, Longfei Yun, Souvik Kundu, Zhengzhong Liu, Eric P. Xing, Hao Zhang:
Scaling Long Context Training Data by Long-Distance Referrals. ICLR 2025 - [c389]Zhenting Qi, Hanlin Zhang, Eric P. Xing, Sham M. Kakade, Himabindu Lakkaraju:
Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems. ICLR 2025 - [c388]Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang, Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, Eric P. Xing, Kun Zhang:
Causal Representation Learning from Multimodal Biomedical Observations. ICLR 2025 - [c387]Aviv Bick, Eric P. Xing, Albert Gu:
Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism. ICML 2025 - [c386]Yuan Li, Zhengzhong Liu, Eric P. Xing:
Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models. ICML 2025 - [c385]Bowen Tan, Zheng Xu, Eric P. Xing, Zhiting Hu, Shanshan Wu:
Synthesizing Privacy-Preserving Text Data via Finetuning *without* Finetuning Billion-Scale LLMs. ICML 2025 - [c384]Shaoan Xie, Lingjing Kong, Yujia Zheng, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang:
Learning Vision and Language Concepts for Controllable Image Generation. ICML 2025 - [c383]Michael Francis Perez, Yichi Yang, Yuheng Zha, Enze Ma, Danish Nisar Ahmed Tamboli, Haodi Ma, Reza Shahriari, Vyom Pathak, Dzmitry Kasinets, Rohith Venkatakrishnan, Daisy Zhe Wang, Jaime Ruiz, Eric D. Ragan, Zhiting Hu, Eric P. Xing, Jun-Yan Zhu:
CReLeRI: Explainable, Concept-centric, Representation, Learning, Reasoning, and Interaction Video Analysis System. ACM Multimedia 2025: 13528-13530 - [i297]Zhengzhong Liu, Bowen Tan, Hongyi Wang, Willie Neiswanger, Tianhua Tao, Haonan Li, Fajri Koto, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Liqun Ma, Liping Tang, Nikhil Ranjan, Yonghao Zhuang, Guowei He, Renxi Wang, Mingkai Deng, Robin Algayres, Yuanzhi Li, Zhiqiang Shen, Preslav Nakov, Eric P. Xing:
LLM360 K2: Building a 65B 360-Open-Source Large Language Model from Scratch. CoRR abs/2501.07124 (2025) - [i296]Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing, Kun Zhang:
Towards Understanding Extrapolation: a Causal Lens. CoRR abs/2501.09163 (2025) - [i295]Wenhao Zheng, Yixiao Chen, Weitong Zhang, Souvik Kundu, Yun Li, Zhengzhong Liu, Eric P. Xing, Hongyi Wang, Huaxiu Yao:
CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing. CoRR abs/2502.01976 (2025) - [i294]Afonso Lourenço, João Gama, Eric P. Xing, Goreti Marreiros:
In-context learning of evolving data streams with tabular foundational models. CoRR abs/2502.16840 (2025) - [i293]Bowen Tan, Zheng Xu, Eric P. Xing, Zhiting Hu, Shanshan Wu:
Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs. CoRR abs/2503.12347 (2025) - [i292]Fan Zhou, Zengzhi Wang, Nikhil Ranjan, Zhoujun Cheng, Liping Tang, Guowei He, Zhengzhong Liu, Eric P. Xing:
MegaMath: Pushing the Limits of Open Math Corpora. CoRR abs/2504.02807 (2025) - [i291]Jianshu She, Wenhao Zheng, Zhengzhong Liu, Hongyi Wang, Eric P. Xing, Huaxiu Yao, Qirong Ho:
Token Level Routing Inference System for Edge Devices. CoRR abs/2504.07878 (2025) - [i290]Aviv Bick, Eric P. Xing, Albert Gu:
Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism. CoRR abs/2504.18574 (2025) - [i289]Yanbin Yin, Kun Zhou, Zhen Wang, Zhaoxiang Zhang, Yifei Shao, Shibo Hao, Yi Gu, Jieyuan Liu, Somanshu Singla, Tianyang Liu, Eric P. Xing, Zhengzhong Liu, Haojian Jin, Zhiting Hu:
Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models. CoRR abs/2505.12808 (2025) - [i288]Lanxiang Hu, Mingjia Huo, Yuxuan Zhang, Haoyang Yu, Eric P. Xing, Ion Stoica, Tajana Rosing, Haojian Jin, Hao Zhang:
lmgame-Bench: How Good are LLMs at Playing Games? CoRR abs/2505.15146 (2025) - [i287]Han Guo, Songlin Yang, Tarushii Goel, Eric P. Xing, Tri Dao, Yoon Kim:
Log-Linear Attention. CoRR abs/2506.04761 (2025) - [i286]Tianjun Yao, Haoxuan Li, Yongqiang Chen, Tongliang Liu, Le Song, Eric P. Xing, Zhiqiang Shen:
Pruning Spurious Subgraphs for Graph Out-of-Distribtuion Generalization. CoRR abs/2506.05957 (2025) - [i285]Zhoujun Cheng, Shibo Hao, Tianyang Liu, Fan Zhou, Yutao Xie, Feng Yao, Yuexin Bian, Yonghao Zhuang, Nilabjo Dey, Yuheng Zha, Yi Gu, Kun Zhou, Yuqi Wang, Yuan Li, Richard Fan, Jianshu She, Chengqian Gao, Abulhair Saparov, Haonan Li, Taylor W. Killian, Mikhail Yurochkin, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective. CoRR abs/2506.14965 (2025) - [i284]Zhenting Qi, Fan Nie, Alexandre Alahi, James Zou, Himabindu Lakkaraju, Yilun Du, Eric P. Xing, Sham M. Kakade, Hanlin Zhang:
EvoLM: In Search of Lost Language Model Training Dynamics. CoRR abs/2506.16029 (2025) - [i283]Guokan Shang, Hadi Abdine, Ahmad Chamma, Amr Mohamed, Mohamed Anwar, Abdelaziz Bounhar, Omar El Harrouss, Preslav Nakov, Michalis Vazirgiannis, Eric P. Xing:
Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts. CoRR abs/2507.04569 (2025) - [i282]Eric P. Xing, Mingkai Deng, Jinyu Hou, Zhiting Hu:
Critiques of World Models. CoRR abs/2507.05169 (2025) - [i281]Shaoan Xie, Lingjing Kong, Yujia Zheng, Yu Yao, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang:
SmartCLIP: Modular Vision-language Alignment with Identification Guarantees. CoRR abs/2507.22264 (2025) - [i280]Mingkai Deng, Jinyu Hou, Yilin Shen, Hongxia Jin, Graham Neubig, Zhiting Hu, Eric P. Xing:
SimuRA: Towards General Goal-Oriented Agent via Simulative Reasoning Architecture with LLM-Based World Model. CoRR abs/2507.23773 (2025) - [i279]Jianshu She, Xinyue Li, Eric P. Xing, Zhengzhong Liu, Qirong Ho:
How Does Controllability Emerge In Language Models During Pretraining? CoRR abs/2508.01892 (2025) - [i278]Chen Li, Chinthani Sugandhika, Ee Yeo Keat, Eric P. Xing, Hao Zhang, Hong Yang, Deepu Rajan, Basura Fernando:
IMoRe: Implicit Program-Guided Reasoning for Human Motion Q&A. CoRR abs/2508.01984 (2025) - [i277]Yuan Li, Zhengzhong Liu, Eric P. Xing:
Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models. CoRR abs/2508.11953 (2025) - [i276]Yuheng Zha, Kun Zhou, Yujia Wu, Yushu Wang, Jie Feng, Zhi Xu, Shibo Hao, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation. CoRR abs/2508.12680 (2025) - [i275]Zhoujun Cheng, Richard Fan, Shibo Hao, Taylor W. Killian, Haonan Li, Suqi Sun, Hector Ren, Alexander Moreno, Daqian Zhang, Tianjun Zhong, Yuxin Xiong, Yuanzhe Hu, Yutao Xie, Xudong Han, Yuqi Wang, Varad Pimpalkhute, Yonghao Zhuang, Aaryamonvikram Singh, Xuezhi Liang, Anze Xie, Jianshu She, Desai Fan, Chengqian Gao, Liqun Ma, Mikhail Yurochkin, John Maggs, Xuezhe Ma, Guowei He, Zhiting Hu, Zhengzhong Liu, Eric P. Xing:
K2-Think: A Parameter-Efficient Reasoning System. CoRR abs/2509.07604 (2025) - [i274]Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing:
Response to Promises and Pitfalls of Deep Kernel Learning. CoRR abs/2509.21228 (2025) - [i273]Shaoan Xie, Lingjing Kong, Xiangchen Song, Xinshuai Dong, Guangyi Chen, Eric P. Xing, Kun Zhang:
Step-Aware Policy Optimization for Reasoning in Diffusion Large Language Models. CoRR abs/2510.01544 (2025) - [i272]Sazan Mahbub, Souvik Kundu, Eric P. Xing:
PRISM: Enhancing Protein Inverse Folding through Fine-Grained Retrieval on Structure-Sequence Multimodal Representations. CoRR abs/2510.11750 (2025) - [i271]Jiannan Xiang, Yi Gu, Zihan Liu, Zeyu Feng, Qiyue Gao, Yiyan Hu, Benhao Huang, Guangyi Liu, Yichi Yang, Kun Zhou, Davit Abrahamyan, Arif Ahmad, Ganesh Bannur, Junrong Chen, Kimi Chen, Mingkai Deng, Ruobing Han, Xinqi Huang, Haoqiang Kang, Zheqi Li, Enze Ma, Hector Ren, Yashowardhan Shinde, Rohan Shingre, Ramsundar Tanikella, Kaiming Tao, Dequan Yang, Xinle Yu, Cong Zeng, Binglin Zhou, Hector Liu, Zhiting Hu, Eric P. Xing:
PAN: A World Model for General, Interactable, and Long-Horizon World Simulation. CoRR abs/2511.09057 (2025) - [i270]Lingjing Kong, Shaoan Xie, Guangyi Chen, Yuewen Sun, Xiangchen Song, Eric P. Xing, Kun Zhang:
Beyond the Black Box: Identifiable Interpretation and Control in Generative Models via Causal Minimality. CoRR abs/2512.10720 (2025) - [i269]Afonso Lourenço, João Gama, Eric P. Xing, Goreti Marreiros:
Bridging Streaming Continual Learning via In-Context Large Tabular Models. CoRR abs/2512.11668 (2025) - 2024
- [j80]Nanqing Dong, Michael Kampffmeyer, Haoyang Su, Eric P. Xing:
An exploratory study of self-supervised pre-training on partially supervised multi-label classification on chest X-ray images. Appl. Soft Comput. 163: 111855 (2024) - [j79]Ding Bai, Caleb N. Ellington, Shentong Mo, Le Song, Eric P. Xing:
AttentionPert: accurately modeling multiplexed genetic perturbations with multi-scale effects. Bioinform. 40(Supplement_1): i453-i461 (2024) - [j78]Gongjie Zhang, Zhipeng Luo, Jiaxing Huang, Shijian Lu, Eric P. Xing:
Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion. Int. J. Comput. Vis. 132(8): 2825-2844 (2024) - [j77]Caleb N. Ellington, Benjamin J. Lengerich, Wesley Lo, Aaron Alvarez, Andrea Rubbi, Manolis Kellis, Eric P. Xing:
Contextualized: Heterogeneous Modeling Toolbox. J. Open Source Softw. 9(97): 6469 (2024) - [j76]Nanqing Dong, Zhipeng Wang, Jiahao Sun, Michael Kampffmeyer, William J. Knottenbelt, Eric P. Xing:
Defending Against Poisoning Attacks in Federated Learning With Blockchain. IEEE Trans. Artif. Intell. 5(7): 3743-3756 (2024) - [j75]Hanlin Zhang, Shuai Lin, Weiyang Liu, Pan Zhou, Jian Tang, Xiaodan Liang, Eric P. Xing:
Iterative Graph Self-Distillation. IEEE Trans. Knowl. Data Eng. 36(3): 1161-1169 (2024) - [j74]Shuai Lin, Chen Liu, Pan Zhou, Zi-Yuan Hu, Shuojia Wang, Ruihui Zhao, Yefeng Zheng, Liang Lin, Eric P. Xing, Xiaodan Liang:
Prototypical Graph Contrastive Learning. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2747-2758 (2024) - [c382]Kirill Vishniakov, Eric P. Xing, Zhiqiang Shen:
MixMask: Revisiting Masking Strategy for Siamese ConvNets. BMVC 2024 - [c381]Hanoona Abdul Rasheed, Muhammad Maaz, Sahal Shaji Mullappilly, Abdelrahman M. Shaker, Salman H. Khan, Hisham Cholakkal, Rao Muhammad Anwer, Eric P. Xing, Ming-Hsuan Yang, Fahad Shahbaz Khan:
GLaMM: Pixel Grounding Large Multimodal Model. CVPR 2024: 13009-13018 - [c380]Adilbek Karmanov, Dayan Guan, Shijian Lu, Abdulmotaleb El Saddik, Eric P. Xing:
Efficient Test-Time Adaptation of Vision-Language Models. CVPR 2024: 14162-14171 - [c379]Jiahui Zhang, Fangneng Zhan, Muyu Xu, Shijian Lu, Eric P. Xing:
FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization. CVPR 2024: 21424-21433 - [c378]Han Guo, William Brandon, Radostin Cholakov, Jonathan Ragan-Kelley, Eric P. Xing, Yoon Kim:
Fast Matrix Multiplications for Lookup Table-Quantized LLMs. EMNLP (Findings) 2024: 12419-12433 - [c377]Somanshu Singla, Zhen Wang, Tianyang Liu, Abdullah Ashfaq, Zhiting Hu, Eric P. Xing:
Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models. EMNLP 2024: 21889-21909 - [c376]Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin:
Fusing Models with Complementary Expertise. ICLR 2024 - [c375]Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim:
LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning. ICLR 2024 - [c374]Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P. Xing, Zhiting Hu:
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization. ICLR 2024 - [c373]Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang:
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. ICLR 2024 - [c372]Jannik Deuschel, Caleb Ellington, Yingtao Luo, Benjamin J. Lengerich, Pascal Friederich, Eric P. Xing:
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. ICML 2024: 10642-10660 - [c371]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024: 20166-20270 - [c370]Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu, Liping Tang, Yuan Gao, Zhen Li, Shuguang Cui, Julian J. McAuley, Zichao Yang, Eric P. Xing, Zhiting Hu:
Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding. ICML 2024: 31964-31993 - [c369]Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman:
Does Compressing Activations Help Model Parallel Training? MLSys 2024 - [c368]Bowen Tan, Yun Zhu, Lijuan Liu, Hongyi Wang, Yonghao Zhuang, Jindong Chen, Eric P. Xing, Zhiting Hu:
RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs. NAACL (Demonstrations) 2024: 137-147 - [c367]Yifan Zhang, Hanlin Zhang, Li Li, Eric P. Xing:
Evaluating Step-by-Step Reasoning through Symbolic Verification. NAACL-HLT (Findings) 2024: 2984-3002 - [c366]Hanlin Zhang, Yifan Zhang, Yaodong Yu, Dhruv Madeka, Dean P. Foster, Eric P. Xing, Himabindu Lakkaraju, Sham M. Kakade:
A Study on the Calibration of In-context Learning. NAACL-HLT 2024: 6118-6136 - [c365]Aviv Bick, Kevin Y. Li, Eric P. Xing, J. Zico Kolter, Albert Gu:
Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. NeurIPS 2024 - [c364]Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang:
Learning Discrete Concepts in Latent Hierarchical Models. NeurIPS 2024 - [c363]Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing, Kun Zhang:
Towards Understanding Extrapolation: a Causal Lens. NeurIPS 2024 - [c362]Sukmin Yun, Haokun Lin, Rusiru Thushara, Mohammad Qazim Bhat, Yongxin Wang, Zutao Jiang, Mingkai Deng, Jinhong Wang, Tianhua Tao, Junbo Li, Haonan Li, Preslav Nakov, Timothy Baldwin, Zhengzhong Liu, Eric P. Xing, Xiaodan Liang, Zhiqiang Shen:
Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs. NeurIPS 2024 - [i268]Jiaxing Huang, Kai Jiang, Jingyi Zhang, Han Qiu, Lewei Lu, Shijian Lu, Eric P. Xing:
Learning to Prompt Segment Anything Models. CoRR abs/2401.04651 (2024) - [i267]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i266]Loka Li, Guangyi Chen, Yusheng Su, Zhenhao Chen, Yixuan Zhang, Eric P. Xing, Kun Zhang:
Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models. CoRR abs/2402.12563 (2024) - [i265]Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang:
Counterfactual Generation with Identifiability Guarantees. CoRR abs/2402.15309 (2024) - [i264]Omkar Thawakar, Ashmal Vayani, Salman H. Khan, Hisham Cholakkal, Rao Muhammad Anwer, Michael Felsberg, Tim Baldwin, Eric P. Xing, Fahad Shahbaz Khan:
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT. CoRR abs/2402.16840 (2024) - [i263]Zhenting Qi, Hanlin Zhang, Eric P. Xing, Sham M. Kakade, Himabindu Lakkaraju:
Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems. CoRR abs/2402.17840 (2024) - [i262]Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu, Liping Tang, Yuan Gao, Zhen Li, Shuguang Cui, Julian J. McAuley, Eric P. Xing, Zichao Yang, Zhiting Hu:
Generating, Reconstructing, and Representing Discrete and Continuous Data: Generalized Diffusion with Learnable Encoding-Decoding. CoRR abs/2402.19009 (2024) - [i261]Jiahui Zhang, Fangneng Zhan, Muyu Xu, Shijian Lu, Eric P. Xing:
FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization. CoRR abs/2403.06908 (2024) - [i260]Adilbek Karmanov, Dayan Guan, Shijian Lu, Abdulmotaleb El Saddik, Eric P. Xing:
Efficient Test-Time Adaptation of Vision-Language Models. CoRR abs/2403.18293 (2024) - [i259]Longfei Yun, Yonghao Zhuang, Yao Fu, Eric P. Xing, Hao Zhang:
Toward Inference-optimal Mixture-of-Expert Large Language Models. CoRR abs/2404.02852 (2024) - [i258]Sang Keun Choe, Hwijeen Ahn, Juhan Bae, Kewen Zhao, Minsoo Kang, Youngseog Chung, Adithya Pratapa, Willie Neiswanger, Emma Strubell, Teruko Mitamura, Jeff G. Schneider, Eduard H. Hovy, Roger B. Grosse, Eric P. Xing:
What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions. CoRR abs/2405.13954 (2024) - [i257]Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang:
Learning Discrete Concepts in Latent Hierarchical Models. CoRR abs/2406.00519 (2024) - [i256]Jiannan Xiang, Guangyi Liu, Yi Gu, Qiyue Gao, Yuting Ning, Yuheng Zha, Zeyu Feng, Tianhua Tao, Shibo Hao, Yemin Shi, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Pandora: Towards General World Model with Natural Language Actions and Video States. CoRR abs/2406.09455 (2024) - [i255]Sukmin Yun, Haokun Lin, Rusiru Thushara, Mohammad Qazim Bhat, Yongxin Wang, Zutao Jiang, Mingkai Deng, Jinhong Wang, Tianhua Tao, Junbo Li, Haonan Li, Preslav Nakov, Timothy Baldwin, Zhengzhong Liu, Eric P. Xing, Xiaodan Liang, Zhiqiang Shen:
Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs. CoRR abs/2406.20098 (2024) - [i254]Han Guo, William Brandon, Radostin Cholakov, Jonathan Ragan-Kelley, Eric P. Xing, Yoon Kim:
Fast Matrix Multiplications for Lookup Table-Quantized LLMs. CoRR abs/2407.10960 (2024) - [i253]Aviv Bick, Kevin Y. Li, Eric P. Xing, J. Zico Kolter, Albert Gu:
Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. CoRR abs/2408.10189 (2024) - [i252]Guokan Shang, Hadi Abdine, Yousef Khoubrane, Amr Mohamed, Yassine Abbahaddou, Sofiane Ennadir, Imane Momayiz, Xuguang Ren, Eric Moulines, Preslav Nakov, Michalis Vazirgiannis, Eric P. Xing:
Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect. CoRR abs/2409.17912 (2024) - [i251]Abdelmajid Essofi, Ridwan Salahuddeen, Munachiso Nwadike, Elnura Zhalieva, Kun Zhang, Eric P. Xing, Willie Neiswanger, Qirong Ho:
Reducing Hyperparameter Tuning Costs in ML, Vision and Language Model Training Pipelines via Memoization-Awareness. CoRR abs/2411.03731 (2024) - [i250]Tianhua Tao, Junbo Li, Bowen Tan, Hongyi Wang, William Marshall, Bhargav Kanakiya, Joel Hestness, Natalia Vassilieva, Zhiqiang Shen, Eric P. Xing, Zhengzhong Liu:
Crystal: Illuminating LLM Abilities on Language and Code. CoRR abs/2411.04156 (2024) - [i249]Shehan Munasinghe, Hanan Gani, Wenqi Zhu, Jiale Cao, Eric P. Xing, Fahad Shahbaz Khan, Salman Khan:
VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos. CoRR abs/2411.04923 (2024) - [i248]Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang, Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, Eric P. Xing, Kun Zhang:
Causal Representation Learning from Multimodal Biological Observations. CoRR abs/2411.06518 (2024) - [i247]Somanshu Singla, Zhen Wang, Tianyang Liu, Abdullah Ashfaq, Zhiting Hu, Eric P. Xing:
Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models. CoRR abs/2411.08733 (2024) - [i246]Ethan Wu, Caleb Ellington, Benjamin J. Lengerich, Eric P. Xing:
Patient-Specific Models of Treatment Effects Explain Heterogeneity in Tuberculosis. CoRR abs/2411.10645 (2024) - [i245]Andrew T. McNutt, Abhinav Adduri, Caleb N. Ellington, Monica T. Dayao, Eric P. Xing, Hosein Mohimani, David Ryan Koes:
SPRINT Enables Interpretable and Ultra-Fast Virtual Screening against Thousands of Proteomes. CoRR abs/2411.15418 (2024) - [i244]Le Song, Eran Segal, Eric P. Xing:
Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating and Programming Biology at All Levels. CoRR abs/2412.06993 (2024) - 2023
- [j73]Gongjie Zhang, Zhipeng Luo, Kaiwen Cui, Shijian Lu, Eric P. Xing:
Meta-DETR: Image-Level Few-Shot Detection With Inter-Class Correlation Exploitation. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 12832-12843 (2023) - [j72]Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Shijian Lu, Lingjie Liu, Adam Kortylewski, Christian Theobalt, Eric P. Xing:
Multimodal Image Synthesis and Editing: The Generative AI Era. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15098-15119 (2023) - [j71]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing:
Federated Partially Supervised Learning With Limited Decentralized Medical Images. IEEE Trans. Medical Imaging 42(7): 1944-1954 (2023) - [j70]Yifan Zhang, Hanlin Zhang, Zachary Chase Lipton, Li Erran Li, Eric P. Xing:
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation. Trans. Mach. Learn. Res. 2023 (2023) - [c361]Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing:
Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. ACL (Findings) 2023: 3062-3077 - [c360]Shibo Hao, Bowen Tan, Kaiwen Tang, Bin Ni, Xiyan Shao, Hengzhe Zhang, Eric P. Xing, Zhiting Hu:
BertNet: Harvesting Knowledge Graphs with Arbitrary Relations from Pretrained Language Models. ACL (Findings) 2023: 5000-5015 - [c359]Kaiwen Cui, Yingchen Yu, Fangneng Zhan, Shengcai Liao, Shijian Lu, Eric P. Xing:
KD-DLGAN: Data Limited Image Generation via Knowledge Distillation. CVPR 2023: 3872-3882 - [c358]Lingjing Kong, Martin Q. Ma, Guangyi Chen, Eric P. Xing, Yuejie Chi, Louis-Philippe Morency, Kun Zhang:
Understanding Masked Autoencoders via Hierarchical Latent Variable Models. CVPR 2023: 7918-7928 - [c357]Kunhao Liu, Fangneng Zhan, Yiwen Chen, Jiahui Zhang, Yingchen Yu, Abdulmotaleb El Saddik, Shijian Lu, Eric P. Xing:
StyleRF: Zero-Shot 3D Style Transfer of Neural Radiance Fields. CVPR 2023: 8338-8348 - [c356]Aoran Xiao, Jiaxing Huang, Weihao Xuan, Ruijie Ren, Kangcheng Liu, Dayan Guan, Abdulmotaleb El Saddik, Shijian Lu, Eric P. Xing:
3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds. CVPR 2023: 9382-9392 - [c355]Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric P. Xing:
Betty: An Automatic Differentiation Library for Multilevel Optimization. ICLR 2023 - [c354]Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing:
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. ICLR 2023 - [c353]Dacheng Li, Hongyi Wang, Rulin Shao, Han Guo, Eric P. Xing, Hao Zhang:
MPCFORMER: Fast, Performant and Provate Transformer Inference with MPC. ICLR 2023 - [c352]Hongyi Wang, Saurabh Agarwal, Pongsakorn U.-Chupala, Yoshiki Tanaka, Eric P. Xing, Dimitris Papailiopoulos:
Cuttlefish: Low-Rank Model Training without All the Tuning. MLSys 2023 - [c351]Yonghao Zhuang, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph Gonzalez, Ion Stoica, Hao Zhang, Hexu Zhao:
On Optimizing the Communication of Model Parallelism. MLSys 2023 - [c350]Sang Keun Choe, Sanket Vaibhav Mehta, Hwijeen Ahn, Willie Neiswanger, Pengtao Xie, Emma Strubell, Eric P. Xing:
Making Scalable Meta Learning Practical. NeurIPS 2023 - [c349]Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang:
Identification of Nonlinear Latent Hierarchical Models. NeurIPS 2023 - [c348]Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang:
FedNAR: Federated Optimization with Normalized Annealing Regularization. NeurIPS 2023 - [c347]Kunhao Liu, Fangneng Zhan, Jiahui Zhang, Muyu Xu, Yingchen Yu, Abdulmotaleb El Saddik, Christian Theobalt, Eric P. Xing, Shijian Lu:
Weakly Supervised 3D Open-vocabulary Segmentation. NeurIPS 2023 - [c346]