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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
- 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) - [c377]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 - [c376]Adilbek Karmanov, Dayan Guan, Shijian Lu, Abdulmotaleb El-Saddik, Eric P. Xing:
Efficient Test-Time Adaptation of Vision-Language Models. CVPR 2024: 14162-14171 - [c375]Jiahui Zhang, Fangneng Zhan, Muyu Xu, Shijian Lu, Eric P. Xing:
FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization. CVPR 2024: 21424-21433 - [c374]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 - [c373]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 - [c372]Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin:
Fusing Models with Complementary Expertise. ICLR 2024 - [c371]Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim:
LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning. ICLR 2024 - [c370]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 - [c369]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 - [c368]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 - [c367]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 - [c366]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 - [c365]Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman:
Does Compressing Activations Help Model Parallel Training? MLSys 2024 - [c364]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 - [c363]Yifan Zhang, Hanlin Zhang, Li Li, Eric P. Xing:
Evaluating Step-by-Step Reasoning through Symbolic Verification. NAACL-HLT (Findings) 2024: 2984-3002 - [c362]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 - [i267]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) - [i266]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) - [i265]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) - [i264]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) - [i263]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) - [i262]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) - [i261]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) - [i260]Jiahui Zhang, Fangneng Zhan, Muyu Xu, Shijian Lu, Eric P. Xing:
FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization. CoRR abs/2403.06908 (2024) - [i259]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) - [i258]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) - [i257]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) - [i256]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) - [i255]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) - [i254]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) - [i253]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) - [i252]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) - [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,