Eric P. Xing

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 427

Top Venues

CoRR

NeurIPS

CVPR

ICML

Publications

Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman
Does Compressing Activations Help Model Parallel Training? MLSys (2024)
Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang
Learning Discrete Concepts in Latent Hierarchical Models. CoRR (2024)
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)
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) (2024)
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 (2024)
Jiahui Zhang, Fangneng Zhan, Muyu Xu, Shijian Lu, Eric P. Xing
FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization. CoRR (2024)
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 (2024)
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 (2024)
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 (2024)
Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang
Counterfactual Generation with Identifiability Guarantees. CoRR (2024)
Jiaxing Huang, Kai Jiang, Jingyi Zhang, Han Qiu, Lewei Lu, Shijian Lu, Eric P. Xing
Learning to Prompt Segment Anything Models. CoRR (2024)
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, Chao Zhang, 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 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 (2024)
Han Guo, William Brandon, Radostin Cholakov, Jonathan Ragan-Kelley, Eric P. Xing, Yoon Kim
Fast Matrix Multiplications for Lookup Table-Quantized LLMs. CoRR (2024)
Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
Fusing Models with Complementary Expertise. ICLR (2024)
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 (2024)
Adilbek Karmanov, Dayan Guan, Shijian Lu, Abdulmotaleb El-Saddik, Eric P. Xing
Efficient Test-Time Adaptation of Vision-Language Models. CoRR (2024)
Longfei Yun, Yonghao Zhuang, Yao Fu, Eric P. Xing, Hao Zhang
Toward Inference-optimal Mixture-of-Expert Large Language Models. CoRR (2024)
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) (2024)
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 (2024)
Hanlin Zhang, Yifan Zhang, Yaodong Yu, Dhruv Madeka, Dean Foster, Eric P. Xing, Himabindu Lakkaraju, Sham M. Kakade
A Study on the Calibration of In-context Learning. NAACL-HLT (2024)
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)
Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim
LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning. ICLR (2024)
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) (2024)
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) (2024)
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 (2024)
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 (2024)
Zeyuan Yin, Eric P. Xing, Zhiqiang Shen
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective. NeurIPS (2023)
Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric P. Xing
Betty: An Automatic Differentiation Library for Multilevel Optimization. ICLR (2023)
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 (2023)
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) (2023)
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 (2023)
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) (2023)
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 (2023)
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)
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)
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)
Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
Fusing Models with Complementary Expertise. CoRR (2023)
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 (2023)
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 (2023)
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 (2023)
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 (2023)
Benjamin J. Lengerich, Caleb N. Ellington, Andrea Rubbi, Manolis Kellis, Eric P. Xing
Contextualized Machine Learning. CoRR (2023)
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 (2023)
Kaiwen Cui, Yingchen Yu, Fangneng Zhan, Shengcai Liao, Shijian Lu, Eric P. Xing
KD-DLGAN: Data Limited Image Generation via Knowledge Distillation. CoRR (2023)
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 (2023)
Kai Zhang, Yutong Dai, Hongyi Wang, Eric P. Xing, Xun Chen, Lichao Sun
Memory-adaptive Depth-wise Heterogenous Federated Learning. CoRR (2023)
Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang
FedNAR: Federated Optimization with Normalized Annealing Regularization. NeurIPS (2023)
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)
Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing
Federated Partially Supervised Learning With Limited Decentralized Medical Images. IEEE Trans. Medical Imaging 42 (7) (2023)
Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
Identification of Nonlinear Latent Hierarchical Models. CoRR (2023)
Zeyuan Yin, Eric P. Xing, Zhiqiang Shen
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective. CoRR (2023)
Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman
Does compressing activations help model parallel training? CoRR (2023)
Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang
FedNAR: Federated Optimization with Normalized Annealing Regularization. CoRR (2023)
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 (2023)
Kaiwen Cui, Yingchen Yu, Fangneng Zhan, Shengcai Liao, Shijian Lu, Eric P. Xing
KD-DLGAN: Data Limited Image Generation via Knowledge Distillation. CVPR (2023)
Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang
Counterfactual Generation with Identifiability Guarantees. NeurIPS (2023)
Dacheng Li, Hongyi Wang, Rulin Shao, Han Guo, Eric P. Xing, Hao Zhang
MPCFORMER: Fast, Performant and Provate Transformer Inference with MPC. ICLR (2023)
Hanlin Zhang, Yi-Fan Zhang, Yaodong Yu, Dhruv Madeka, Dean Foster, Eric P. Xing, Hima Lakkaraju, Sham M. Kakade
A Study on the Calibration of In-context Learning. CoRR (2023)
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 (2023)
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)
Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. CoRR (2023)
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)
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)
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)
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 (2023)
Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
Identification of Nonlinear Latent Hierarchical Models. NeurIPS (2023)
Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing
Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. CoRR (2023)
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)
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)
Arnav Chavan, Zhuang Liu, Deepak K. Gupta, Eric P. Xing, Zhiqiang Shen
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning. CoRR (2023)
Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing
Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. ACL (Findings) (2023)
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)
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 (2023)
Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim
LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning. CoRR (2023)
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 (2023)
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)
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 (2022)
Zhiqiang Shen, Eric P. Xing
A Fast Knowledge Distillation Framework for Visual Recognition. ECCV (24) (2022)
Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. CoRR (2022)
Shibo Hao, Bowen Tan, Kaiwen Tang, Hengzhe Zhang, Eric P. Xing, Zhiting Hu
BertNet: Harvesting Knowledge Graphs from Pretrained Language Models. CoRR (2022)
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)
Yifan Zhong, Haohan Wang, Eric P. Xing
MRCLens: an MRC Dataset Bias Detection Toolkit. CoRR (2022)
Zhiqiang Shen, Zechun Liu, Eric P. Xing
Sliced Recursive Transformer. ECCV (24) (2022)
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)
Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric P. Xing, Pengtao Xie
Learning from Mistakes - a Framework for Neural Architecture Search. AAAI (2022)
Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric P. Xing
Betty: An Automatic Differentiation Library for Multilevel Optimization. CoRR (2022)
Kirill Vishniakov, Eric P. Xing, Zhiqiang Shen
MixMask: Revisiting Masked Siamese Self-supervised Learning in Asymmetric Distance. CoRR (2022)
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 (2022)
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)
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)
Haohan Wang, Oscar Lopez, Eric P. Xing, Wei Wu
Kernel Mixed Model for Transcriptome Association Study. J. Comput. Biol. 29 (12) (2022)
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 (2022)
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 (2022)
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 (2022)
Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. KDD (2022)
Hanlin Zhang, Yi-Fan Zhang, Li Erran Li, Eric P. Xing
The Impact of Symbolic Representations on In-context Learning for Few-shot Reasoning. CoRR (2022)
Gongjie Zhang, Zhipeng Luo, Kaiwen Cui, Shijian Lu, Eric P. Xing
Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitation. CoRR (2022)
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) (2022)
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 (2022)
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)

Eric P. Xing.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Eric P. Xing