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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
- 2025
[j81]Reza Shahriari
, Yichi Yang, Danish Nisar Ahmed Tamboli, Michael 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)- [c392]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 - [c391]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 - [c390]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 - [c389]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 - [c388]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 - [c387]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 - [c386]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 - [c385]Yuan Li, Zhengzhong Liu, Eric P. Xing:
Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models. ICML 2025 - [c384]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 - [c383]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 - [i298]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) - [i297]Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing, Kun Zhang:
Towards Understanding Extrapolation: a Causal Lens. CoRR abs/2501.09163 (2025) - [i296]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) - [i295]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) - [i294]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) - [i293]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) - [i292]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) - [i291]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) - [i290]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) - [i289]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) - [i288]Han Guo, Songlin Yang, Tarushii Goel, Eric P. Xing, Tri Dao, Yoon Kim:
Log-Linear Attention. CoRR abs/2506.04761 (2025) - [i287]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) - [i286]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) - [i285]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) - [i284]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) - [i283]Eric P. Xing, Mingkai Deng, Jinyu Hou, Zhiting Hu:
Critiques of World Models. CoRR abs/2507.05169 (2025) - [i282]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) - [i281]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) - [i280]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) - [i279]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) - [i278]Yuan Li, Zhengzhong Liu, Eric P. Xing:
Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models. CoRR abs/2508.11953 (2025) - [i277]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) - [i276]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) - [i275]Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing:
Response to Promises and Pitfalls of Deep Kernel Learning. CoRR abs/2509.21228 (2025) - [i274]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) - [i273]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) - [i272]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) - [i271]Zhengzhong Liu, Liping Tang, Linghao Jin, Haonan Li, Nikhil Ranjan, Desai Fan, Shaurya Rohatgi, Richard Fan, Omkar Pangarkar, Huijuan Wang, Zhoujun Cheng, Suqi Sun, Seungwook Han, Bowen Tan, Gurpreet Gosal, Xudong Han, Varad Pimpalkhute, Shibo Hao, Ming Shan Hee, Joel Hestness, Haolong Jia, Liqun Ma, Aaryamonvikram Singh, Daria Soboleva, Natalia Vassilieva, Renxi Wang, Yingquan Wu, Yuekai Sun, Taylor W. Killian, Alexander Moreno, John Maggs, Hector Ren, Guowei He, Hongyi Wang, Xuezhe Ma, Yuqi Wang, Mikhail Yurochkin, Eric P. Xing:
K2-V2: A 360-Open, Reasoning-Enhanced LLM. CoRR abs/2512.06201 (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 - [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 - [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 - [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]Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric P. Xing, Kun Zhang:
Temporally Disentangled Representation Learning under Unknown Nonstationarity. NeurIPS 2023 - [c345]Bowen Tan, Yun Zhu, Lijuan Liu, Eric P. Xing, Zhiting Hu, Jindong Chen:
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer. NeurIPS 2023 - [c344]Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang:
Counterfactual Generation with Identifiability Guarantees. NeurIPS 2023 - [c343]Zeyuan Yin, Eric P. Xing, Zhiqiang Shen:
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective. NeurIPS 2023 - [c342]Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica:
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. NeurIPS 2023 - [p1]Bowen Tan, Shibo Hao, Eric P. Xing, Zhiting Hu:
Neural-Symbolic Interaction and Co-Evolving. Compendium of Neurosymbolic Artificial Intelligence 2023: 125-152 - [i243]Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman:
Does compressing activations help model parallel training? CoRR abs/2301.02654 (2023) - [i242]Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing:
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. CoRR abs/2302.04228 (2023) - [i241]Kai Zhang, Yutong Dai, Hongyi Wang, Eric P. Xing, Xun Chen, Lichao Sun:
Memory-adaptive Depth-wise Heterogenous Federated Learning. CoRR abs/2303.04887 (2023) - [i240]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. CoRR abs/2303.10598 (2023) - [i239]Kaiwen Cui, Yingchen Yu, Fangneng Zhan, Shengcai Liao, Shijian Lu, Eric P. Xing:
KD-DLGAN: Data Limited Image Generation via Knowledge Distillation. CoRR abs/2303.17158 (2023) - [i238]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. CoRR abs/2304.00690 (2023) - [i237]Hongyi Wang, Saurabh Agarwal, Pongsakorn U.-Chupala, Yoshiki Tanaka, Eric P. Xing, Dimitris S. Papailiopoulos:
Cuttlefish: Low-Rank Model Training without All the Tuning. CoRR abs/2305.02538 (2023) - [i236]Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing:
Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. CoRR abs/2305.03742 (2023) - [i235]Kunhao Liu, Fangneng Zhan, Jiahui Zhang, Muyu Xu, Yingchen Yu, Abdulmotaleb El-Saddik, Christian Theobalt, Eric P. Xing, Shijian Lu:
3D Open-vocabulary Segmentation with Foundation Models. CoRR abs/2305.14093 (2023) - [i234]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. CoRR abs/2306.04898 (2023) - [i233]Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica:
Judging LLM-as-a-judge with MT-Bench and Chatbot Arena. CoRR abs/2306.05685 (2023) - [i232]Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang:
Identification of Nonlinear Latent Hierarchical Models. CoRR abs/2306.07916 (2023) - [i231]Arnav Chavan, Zhuang Liu, Deepak K. Gupta, Eric P. Xing, Zhiqiang Shen:
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning. CoRR abs/2306.07967 (2023) - [i230]Zeyuan Yin, Eric P. Xing, Zhiqiang Shen:
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective. CoRR abs/2306.13092 (2023) - [i229]Nanqing Dong, Zhipeng Wang, Jiahao Sun, Michael Kampffmeyer, Yizhe Wen, Shuoying Zhang, William J. Knottenbelt, Eric P. Xing:
Defending Against Malicious Behaviors in Federated Learning with Blockchain. CoRR abs/2307.00543 (2023) - [i228]Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, Satheesh Katipomu, Haonan Li, Fajri Koto, Osama Mohammed Afzal, Samta Kamboj, Onkar Pandit, Rahul Pal, Lalit Pradhan, Zain Muhammad Mujahid, Massa Baali, Alham Fikri Aji, Zhengzhong Liu, Andy Hock, Andrew Feldman, Jonathan Lee, Andrew Jackson, Preslav Nakov, Timothy Baldwin, Eric P. Xing:
Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models. CoRR abs/2308.16149 (2023) - [i227]Zhiqiang Shen, Tianhua Tao, Liqun Ma, Willie Neiswanger, Zhengzhong Liu, Hongyi Wang, Bowen Tan, Joel Hestness, Natalia Vassilieva, Daria Soboleva, Eric P. Xing:
SlimPajama-DC: Understanding Data Combinations for LLM Training. CoRR abs/2309.10818 (2023) - [i226]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. CoRR abs/2309.11998 (2023) - [i225]Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin:
Fusing Models with Complementary Expertise. CoRR abs/2310.01542 (2023) - [i224]Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang:
FedNAR: Federated Optimization with Normalized Annealing Regularization. CoRR abs/2310.03163 (2023) - [i223]Dacheng Li, Rulin Shao, Anze Xie, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Xuezhe Ma, Hao Zhang:
LightSeq: Sequence Level Parallelism for Distributed Training of Long Context Transformers. CoRR abs/2310.03294 (2023) - [i222]Sang Keun Choe, Sanket Vaibhav Mehta, Hwijeen Ahn, Willie Neiswanger, Pengtao Xie, Emma Strubell, Eric P. Xing:
Making Scalable Meta Learning Practical. CoRR abs/2310.05674 (2023) - [i221]Jannik Deuschel, Caleb N. Ellington, Benjamin J. Lengerich, Yingtao Luo, Pascal Friederich, Eric P. Xing:
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. CoRR abs/2310.07918 (2023) - [i220]Benjamin J. Lengerich, Caleb N. Ellington, Andrea Rubbi, Manolis Kellis, Eric P. Xing:
Contextualized Machine Learning. CoRR abs/2310.11340 (2023) - [i219]Bowen Tan, Yun Zhu, Lijuan Liu, Hongyi Wang, Yonghao Zhuang, Jindong Chen, Eric P. Xing, Zhiting Hu:
Redco: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs. CoRR abs/2310.16355 (2023) - [i218]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. CoRR abs/2310.16427 (2023) - [i217]Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric P. Xing, Kun Zhang:
Temporally Disentangled Representation Learning under Unknown Nonstationarity. CoRR abs/2310.18615 (2023) - [i216]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. CoRR abs/2311.03356 (2023) - [i215]Bowen Tan, Yun Zhu, Lijuan Liu, Eric P. Xing, Zhiting Hu, Jindong Chen:
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer. CoRR abs/2311.06720 (2023) - [i214]Yuxin Pei, Pushkar Bhuse, Zhengzhong Liu, Eric P. Xing:
SegMix: A Simple Structure-Aware Data Augmentation Method. CoRR abs/2311.09505 (2023) - [i213]Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim:
LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning. CoRR abs/2311.12023 (2023) - [i212]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. CoRR abs/2312.04021 (2023) - [i211]Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Xuguang Ren, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Tim Baldwin, Eric P. Xing:
LLM360: Towards Fully Transparent Open-Source LLMs. CoRR abs/2312.06550 (2023) - 2022
- [j69]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric P. Xing:
Towards robust partially supervised multi-structure medical image segmentation on small-scale data. Appl. Soft Comput. 114: 108074 (2022) - [j68]Haohan Wang, Bryon Aragam, Eric P. Xing:
Trade-offs of Linear Mixed Models in Genome-Wide Association Studies. J. Comput. Biol. 29(3): 233-242 (2022) - [j67]Haohan Wang, Oscar Lopez, Eric P. Xing, Wei Wu:
Kernel Mixed Model for Transcriptome Association Study. J. Comput. Biol. 29(12): 1353-1356 (2022) - [j66]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing:
Negational symmetry of quantum neural networks for binary pattern classification. Pattern Recognit. 129: 108750 (2022) - [j65]Zeya Wang, Yang Ni, Baoyu Jing, Deqing Wang, Hao Zhang, Eric P. Xing:
DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7610-7620 (2022) - [c341]Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Poe Xing:
Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning. AAAI 2022: 2216-2224 - [c340]Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric P. Xing, Pengtao Xie:
Learning from Mistakes - a Framework for Neural Architecture Search. AAAI 2022: 10184-10192 - [c339]Benjamin J. Lengerich, Eric P. Xing, Rich Caruana:
Dropout as a Regularizer of Interaction Effects. AISTATS 2022: 7550-7564 - [c338]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CVPR 2022: 4921-4931 - [c337]Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen:
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. CVPR 2022: 4932-4942 - [c336]Hanlin Zhang, Yifan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing:
Towards Principled Disentanglement for Domain Generalization. CVPR 2022: 8014-8024 - [c335]Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing:
The Two Dimensions of Worst-case Training and Their Integrated Effect for Out-of-domain Generalization. CVPR 2022: 9621-9631 - [c334]Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner:
Data-Free Neural Architecture Search via Recursive Label Calibration. ECCV (24) 2022: 391-406 - [c333]Zhiqiang Shen, Eric P. Xing:
A Fast Knowledge Distillation Framework for Visual Recognition. ECCV (24) 2022: 673-690 - [c332]Zhiqiang Shen, Zechun Liu, Eric P. Xing:
Sliced Recursive Transformer. ECCV (24) 2022: 727-744 - [c331]Jiannan Xiang, Zhengzhong Liu, Yucheng Zhou, Eric P. Xing, Zhiting Hu:
ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models. EMNLP (Findings) 2022: 1886-1899 - [c330]Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, Yihan Wang, Han Guo, Tianmin Shu, Meng Song, Eric P. Xing, Zhiting Hu:
RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning. EMNLP 2022: 3369-3391 - [c329]Han Guo, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Efficient (Soft) Q-Learning for Text Generation with Limited Good Data. EMNLP (Findings) 2022: 6969-6991 - [c328]Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng:
SDQ: Stochastic Differentiable Quantization with Mixed Precision. ICML 2022: 9295-9309 - [c327]Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing:
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. KDD 2022: 1846-1856 - [c326]Jiaxing Huang, Kaiwen Cui, Dayan Guan, Aoran Xiao, Fangneng Zhan, Shijian Lu, Shengcai Liao, Eric P. Xing:
Masked Generative Adversarial Networks are Data-Efficient Generation Learners. NeurIPS 2022 - [c325]Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang:
AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness. NeurIPS 2022 - [c324]Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Eric P. Xing, Kangwook Lee, Dimitris S. Papailiopoulos:
Rare Gems: Finding Lottery Tickets at Initialization. NeurIPS 2022 - [c323]Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica:
Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. OSDI 2022: 559-578 - [c322]Haohan Wang, Oscar L. Lopez, Wei Wu, Eric P. Xing:
Gene Set Priorization Guided by Regulatory Networks with p-values through Kernel Mixed Model. RECOMB 2022: 107-125 - [c321]Haohan Wang, Zeyi Huang, Hanlin Zhang, Yong Jae Lee, Eric P. Xing:
Toward learning human-aligned cross-domain robust models by countering misaligned features. UAI 2022: 2075-2084 - [i210]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CoRR abs/2201.00814 (2022) - [i209]Liu Ziyin, Hanlin Zhang, Xiangming Meng, Yuting Lu, Eric P. Xing, Masahito Ueda:
Stochastic Neural Networks with Infinite Width are Deterministic. CoRR abs/2201.12724 (2022) - [i208]Yifan Zhang, Hanlin Zhang, Zachary C. Lipton, Li Erran Li, Eric P. Xing:
Can Transformers be Strong Treatment Effect Estimators? CoRR abs/2202.01336 (2022) - [i207]Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing:
The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization. CoRR abs/2204.04384 (2022) - [i206]Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, Yihan Wang, Han Guo, Tianmin Shu, Meng Song, Eric P. Xing, Zhiting Hu:
RLPrompt: Optimizing Discrete Text Prompts With Reinforcement Learning. CoRR abs/2205.12548 (2022) - [i205]Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing:
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. CoRR abs/2206.01909 (2022) - [i204]Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng:
SDQ: Stochastic Differentiable Quantization with Mixed Precision. CoRR abs/2206.04459 (2022) - [i203]Shibo Hao, Bowen Tan, Kaiwen Tang, Hengzhe Zhang, Eric P. Xing, Zhiting Hu:
BertNet: Harvesting Knowledge Graphs from Pretrained Language Models. CoRR abs/2206.14268 (2022) - [i202]Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric P. Xing:
Betty: An Automatic Differentiation Library for Multilevel Optimization. CoRR abs/2207.02849 (2022) - [i201]Yifan Zhong, Haohan Wang, Eric P. Xing:
MRCLens: an MRC Dataset Bias Detection Toolkit. CoRR abs/2207.08943 (2022) - [i200]Chonghan Chen, Haohan Wang, Leyang Hu, Yuhao Zhang, Shuguang Lyu, Jingcheng Wu, Xinnuo Li, Linjing Sun, Eric P. Xing:
Robustar: Interactive Toolbox Supporting Precise Data Annotation for Robust Vision Learning. CoRR abs/2207.08944 (2022) - [i199]Gongjie Zhang, Zhipeng Luo, Yingchen Yu, Jiaxing Huang, Kaiwen Cui, Shijian Lu, Eric P. Xing:
Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion. CoRR abs/2207.14172 (2022) - [i198]Gongjie Zhang, Zhipeng Luo, Kaiwen Cui, Shijian Lu, Eric P. Xing:
Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitation. CoRR abs/2208.00219 (2022) - [i197]Jiannan Xiang, Zhengzhong Liu, Yucheng Zhou, Eric P. Xing, Zhiting Hu:
ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models. CoRR abs/2210.04325 (2022) - [i196]Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang:
AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness. CoRR abs/2210.07297 (2022) - [i195]Kirill Vishniakov, Eric P. Xing, Zhiqiang Shen:
MixMask: Revisiting Masked Siamese Self-supervised Learning in Asymmetric Distance. CoRR abs/2210.11456 (2022) - [i194]Dacheng Li, Rulin Shao, Hongyi Wang, Han Guo, Eric P. Xing, Hao Zhang:
MPCFormer: fast, performant and private Transformer inference with MPC. CoRR abs/2211.01452 (2022) - [i193]Yonghao Zhuang, Hexu Zhao, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph E. Gonzalez, Ion Stoica, Hao Zhang:
On Optimizing the Communication of Model Parallelism. CoRR abs/2211.05322 (2022) - [i192]Minh-Long Luu, Zeyi Huang, Eric P. Xing, Yong Jae Lee, Haohan Wang:
Expeditious Saliency-guided Mix-up through Random Gradient Thresholding. CoRR abs/2212.04875 (2022) - [i191]Hanlin Zhang, Yifan Zhang, Li Erran Li, Eric P. Xing:
The Impact of Symbolic Representations on In-context Learning for Few-shot Reasoning. CoRR abs/2212.08686 (2022) - 2021
- [j64]Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric P. Xing, Min Xu:
Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography. Bioinform. 37(16): 2340-2346 (2021) - [j63]Haohan Wang, Fen Pei, Michael M. Vanyukov, Ivet Bahar, Wei Wu, Eric P. Xing:
Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets. BMC Bioinform. 22(1): 50 (2021) - [j62]Songwei Ge, Haohan Wang, Amir Alavi, Eric P. Xing, Ziv Bar-Joseph:
Supervised Adversarial Alignment of Single-Cell RNA-seq Data. J. Comput. Biol. 28(5): 501-513 (2021) - [c320]Seo-Jin Bang, Pengtao Xie, Heewook Lee, Wei Wu, Eric P. Xing:
Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach. AAAI 2021: 11396-11404 - [c319]Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric P. Xing, Liang Lin:
GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning. ACL/IJCNLP (Findings) 2021: 513-523 - [c318]Xuehai He, Zhuo Cai, Wenlan Wei, Yichen Zhang, Luntian Mou, Eric P. Xing, Pengtao Xie:
Towards Visual Question Answering on Pathology Images. ACL/IJCNLP (2) 2021: 708-718 - [c317]Meng Zhou, Zechen Li, Bowen Tan, Guangtao Zeng, Wenmian Yang, Xuehai He, Zeqian Ju, Subrato Chakravorty, Shu Chen, Xingyi Yang, Yichen Zhang, Qingyang Wu, Zhou Yu, Kun Xu, Eric P. Xing, Pengtao Xie:
On the Generation of Medical Dialogs for COVID-19. ACL/IJCNLP (2) 2021: 886-896 - [c316]Maruan Al-Shedivat, Liam Li, Eric P. Xing, Ameet Talwalkar:
On Data Efficiency of Meta-learning. AISTATS 2021: 1369-1377 - [c315]Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing:
Knowledge-Aware Meta-learning for Low-Resource Text Classification. EMNLP (1) 2021: 1814-1821 - [c314]Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation. EMNLP (1) 2021: 7580-7605 - [c313]Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. ICLR 2021 - [c312]Benedikt Boecking, Willie Neiswanger, Eric P. Xing, Artur Dubrawski:
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling. ICLR 2021 - [c311]Bowen Tan, Zichao Yang, Maruan Al-Shedivat, Eric P. Xing, Zhiting Hu:
Progressive Generation of Long Text with Pretrained Language Models. NAACL-HLT 2021: 4313-4324 - [c310]Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song:
Multi-task Learning of Order-Consistent Causal Graphs. NeurIPS 2021: 11083-11095 - [c309]Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing:
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. OSDI 2021 - [i190]Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava J. Newman, Sujoy Ganguly, Danny Lange, Atilim Günes Baydin, Amit Sharma, Adam Gibson, Yarin Gal, Eric P. Xing, Chris Mattmann, James Parr:
Technology Readiness Levels for Machine Learning Systems. CoRR abs/2101.03989 (2021) - [i189]Maruan Al-Shedivat, Liam Li, Eric Poe Xing, Ameet Talwalkar:
On Data Efficiency of Meta-learning. CoRR abs/2102.00127 (2021) - [i188]Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric Poe Xing, Min Xu:
Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography. CoRR abs/2102.12040 (2021) - [i187]Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu:
A Data-Centric Framework for Composable NLP Workflows. CoRR abs/2103.01834 (2021) - [i186]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing:
Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification. CoRR abs/2105.09580 (2021) - [i185]Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric P. Xing, Liang Lin:
GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning. CoRR abs/2105.14517 (2021) - [i184]Han Guo, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Text Generation with Efficient (Soft) Q-Learning. CoRR abs/2106.07704 (2021) - [i183]Yuxin Xiao, Eric P. Xing, Willie Neiswanger:
Amortized Auto-Tuning: Cost-Efficient Transfer Optimization for Hyperparameter Recommendation. CoRR abs/2106.09179 (2021) - [i182]Shuai Lin, Pan Zhou, Zi-Yuan Hu, Shuojia Wang, Ruihui Zhao, Yefeng Zheng, Liang Lin, Eric P. Xing, Xiaodan Liang:
Prototypical Graph Contrastive Learning. CoRR abs/2106.09645 (2021) - [i181]Zhiting Hu, Eric P. Xing:
Panoramic Learning with A Standardized Machine Learning Formalism. CoRR abs/2108.07783 (2021) - [i180]Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing:
Knowledge-Aware Meta-learning for Low-Resource Text Classification. CoRR abs/2109.04707 (2021) - [i179]Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation. CoRR abs/2109.06379 (2021) - [i178]Zhaoming Qin, Nanqing Dong, Eric P. Xing, Junwei Cao:
Cooperative Multi-Agent Actor-Critic for Privacy-Preserving Load Scheduling in a Residential Microgrid. CoRR abs/2110.02784 (2021) - [i177]Shentong Mo, Xi Fu, Chenyang Hong, Yizhen Chen, Yuxuan Zheng, Xiangru Tang, Zhiqiang Shen, Eric P. Xing, Yanyan Lan:
Multi-modal Self-supervised Pre-training for Regulatory Genome Across Cell Types. CoRR abs/2110.05231 (2021) - [i176]Benjamin J. Lengerich, Caleb Ellington, Bryon Aragam, Eric P. Xing, Manolis Kellis:
NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters. CoRR abs/2111.01104 (2021) - [i175]Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song:
Multi-task Learning of Order-Consistent Causal Graphs. CoRR abs/2111.02545 (2021) - [i174]Haohan Wang, Bryon Aragam, Eric P. Xing:
Tradeoffs of Linear Mixed Models in Genome-wide Association Studies. CoRR abs/2111.03739 (2021) - [i173]Haohan Wang, Zeyi Huang, Hanlin Zhang, Eric Poe Xing:
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features. CoRR abs/2111.03740 (2021) - [i172]Zhiqiang Shen, Zechun Liu, Eric P. Xing:
Sliced Recursive Transformer. CoRR abs/2111.05297 (2021) - [i171]Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric P. Xing, Pengtao Xie:
Learning from Mistakes - A Framework for Neural Architecture Search. CoRR abs/2111.06353 (2021) - [i170]Hanlin Zhang, Yifan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing:
Towards Principled Disentanglement for Domain Generalization. CoRR abs/2111.13839 (2021) - [i169]Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen:
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. CoRR abs/2111.14826 (2021) - [i168]Zhiqiang Shen, Eric P. Xing:
A Fast Knowledge Distillation Framework for Visual Recognition. CoRR abs/2112.01528 (2021) - [i167]Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner:
Data-Free Neural Architecture Search via Recursive Label Calibration. CoRR abs/2112.02086 (2021) - 2020
- [j61]Shreya Kadambi, Zeya Wang, Eric P. Xing:
WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images. Int. J. Comput. Assist. Radiol. Surg. 15(7): 1205-1213 (2020) - [j60]Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing:
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. J. Mach. Learn. Res. 21: 81:1-81:27 (2020) - [j59]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Contextual Explanation Networks. J. Mach. Learn. Res. 21: 194:1-194:44 (2020) - [j58]Kevin Tran, Willie Neiswanger, Junwoong Yoon, Qingyang Zhang, Eric P. Xing, Zachary W. Ulissi:
Methods for comparing uncertainty quantifications for material property predictions. Mach. Learn. Sci. Technol. 1(2): 25006 (2020) - [j57]Yumin Zheng, Haohan Wang, Yang Zhang, Xin Gao, Eric P. Xing, Min Xu:
Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species. PLoS Comput. Biol. 16(11): 1008297 (2020) - [j56]Yujia Zhang, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing:
Unsupervised object-level video summarization with online motion auto-encoder. Pattern Recognit. Lett. 130: 376-385 (2020) - [c308]Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabás Póczos, Jeff Schneider, Eric P. Xing:
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations. AISTATS 2020: 3393-3403 - [c307]Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing:
Learning Sparse Nonparametric DAGs. AISTATS 2020: 3414-3425 - [c306]Kumar Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead Williamson:
Distributed, partially collapsed MCMC for Bayesian Nonparametrics. AISTATS 2020: 3685-3695 - [c305]Haohan Wang, Xindi Wu, Zeyi Huang, Eric P. Xing:
High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks. CVPR 2020: 8681-8691 - [c304]Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric P. Xing:
Adversarial Domain Adaptation Being Aware of Class Relationships. ECAI 2020: 1579-1586 - [c303]Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang:
Self-challenging Improves Cross-Domain Generalization. ECCV (2) 2020: 124-140 - [c302]Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu:
A Data-Centric Framework for Composable NLP Workflows. EMNLP (Demos) 2020: 197-204 - [c301]Shuai Lin, Wentao Wang, Zichao Yang, Xiaodan Liang, Frank F. Xu, Eric P. Xing, Zhiting Hu:
Record-to-Text Generation with Style Imitation. EMNLP (Findings) 2020: 1589-1598 - [c300]Bowen Tan, Lianhui Qin, Eric P. Xing, Zhiting Hu:
Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach. EMNLP (1) 2020: 6301-6309 - [c299]