Xing, Eric

68 publications

CVPR 2025 ConText-CIR: Learning from Concepts in Text for Composed Image Retrieval Eric Xing, Pranavi Kolouju, Robert Pless, Abby Stylianou, Nathan Jacobs

ICML 2025 Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models Yuan Li, Zhengzhong Liu, Eric Xing

ICCV 2025 Global and Local Entailment Learning for Natural World Imagery Srikumar Sastry, Aayush Dhakal, Eric Xing, Subash Khanal, Nathan Jacobs

CVPRW 2025 Good4cir: Generating Detailed Synthetic Captions for Composed Image Retrieval Pranavi Kolouju, Eric Xing, Robert Pless, Nathan Jacobs, Abby Stylianou

ICML 2025 Learning Vision and Language Concepts for Controllable Image Generation Shaoan Xie, Lingjing Kong, Yujia Zheng, Zeyu Tang, Eric Xing, Guangyi Chen, Kun Zhang

NeurIPS 2025 QuARI: Query Adaptive Retrieval Improvement Eric Xing, Abby Stylianou, Robert Pless, Nathan Jacobs

CVPR 2025 RANGE: Retrieval Augmented Neural Fields for Multi-Resolution Geo-Embeddings Aayush Dhakal, Srikumar Sastry, Subash Khanal, Adeel Ahmad, Eric Xing, Nathan Jacobs

ICML 2025 Synthesizing Privacy-Preserving Text Data via Finetuning *without* Finetuning Billion-Scale LLMs Bowen Tan, Zheng Xu, Eric Xing, Zhiting Hu, Shanshan Wu

ICCV 2025 Towards Open-World Generation of Stereo Images and Unsupervised Matching Feng Qiao, Zhexiao Xiong, Eric Xing, Nathan Jacobs

ICML 2025 Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism Aviv Bick, Eric Xing, Albert Gu

CVPR 2025 VideoGLaMM : A Large Multimodal Model for Pixel-Level Visual Grounding in Videos Shehan Munasinghe, Hanan Gani, Wenqi Zhu, Jiale Cao, Eric Xing, Fahad Shahbaz Khan, Salman Khan

AAAI 2024 ALISON: Fast and Effective Stylometric Authorship Obfuscation Eric Xing, Saranya Venkatraman, Thai Le, Dongwon Lee

CVPR 2024 Efficient Test-Time Adaptation of Vision-Language Models Adilbek Karmanov, Dayan Guan, Shijian Lu, Abdulmotaleb El Saddik, Eric Xing

CVPR 2024 FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization Jiahui Zhang, Fangneng Zhan, Muyu Xu, Shijian Lu, Eric Xing

ICLR 2024 Fusing Models with Complementary Expertise Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric Xing, Mikhail Yurochkin

CVPR 2024 GLaMM: Pixel Grounding Large Multimodal Model Hanoona Rasheed, Muhammad Maaz, Sahal Shaji, Abdelrahman Shaker, Salman Khan, Hisham Cholakkal, Rao M. Anwer, Eric Xing, Ming-Hsuan Yang, Fahad S. Khan

ICLR 2024 LMSYS-Chat-1m: A Large-Scale Real-World LLM Conversation Dataset Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang

ICLR 2024 LQ-LoRA: Low-Rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning Han Guo, Philip Greengard, Eric Xing, Yoon Kim

ICLR 2024 PromptAgent: Strategic Planning with Language Models Enables Expert-Level Prompt Optimization Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric Xing, Zhiting Hu

ICLR 2023 Betty: An Automatic Differentiation Library for Multilevel Optimization Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric Xing

NeurIPSW 2023 Contextualized Networks Reveal Heterogeneous Transcriptomic Regulation in Tumors at Sample-Specific Resolution Caleb Ellington, Ben Lengerich, Thomas Watkins, Jiekun Yang, Hanxi Xiao, Manolis Kellis, Eric Xing

TMLR 2023 Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation YiFan Zhang, Hanlin Zhang, Zachary Chase Lipton, Li Erran Li, Eric Xing

ICLR 2023 Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric Xing

ICLR 2023 Mpcformer: Fast, Performant and Private Transformer Inference with Mpc Dacheng Li, Hongyi Wang, Rulin Shao, Han Guo, Eric Xing, Hao Zhang

AISTATS 2022 Dropout as a Regularizer of Interaction Effects Benjamin J. Lengerich, Eric Xing, Rich Caruana

ECCV 2022 A Fast Knowledge Distillation Framework for Visual Recognition Zhiqiang Shen, Eric Xing

NeurIPSW 2022 Betty: An Automatic Differentiation Library for Multilevel Optimization Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric Xing

ECCV 2022 Data-Free Neural Architecture Search via Recursive Label Calibration Zechun Liu, Zhiqiang Shen, Yun Long, Eric Xing, Kwang-Ting Cheng, Chas Leichner

NeurIPSW 2022 Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation YiFan Zhang, Hanlin Zhang, Zachary Chase Lipton, Li Erran Li, Eric Xing

ICMLW 2022 Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming Hanlin Zhang, Ziyang Li, Jiani Huang, Mayur Naik, Eric Xing

ICML 2022 SDQ: Stochastic Differentiable Quantization with Mixed Precision Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Hu Xianghong, Jeffry Wicaksana, Eric Xing, Kwang-Ting Cheng

ECCV 2022 Sliced Recursive Transformer Zhiqiang Shen, Zechun Liu, Eric Xing

NeurIPSW 2022 The Impact of Symbolic Representations on In-Context Learning for Few-Shot Reasoning Hanlin Zhang, YiFan Zhang, Li Erran Li, Eric Xing

AISTATS 2021 On Data Efficiency of Meta-Learning Maruan Al-Shedivat, Liam Li, Eric Xing, Ameet Talwalkar

ICLR 2021 Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms Maruan Al-Shedivat, Jennifer Gillenwater, Eric Xing, Afshin Rostamizadeh

ICLR 2021 Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling Benedikt Boecking, Willie Neiswanger, Eric Xing, Artur Dubrawski

NeurIPSW 2021 Multi-Modal Self-Supervised Pre-Training for Large-Scale Genome Data Shentong Mo, Xi Fu, Chenyang Hong, Yizhen Chen, Yuxuan Zheng, Xiangru Tang, Yanyan Lan, Zhiqiang Shen, Eric Xing

AISTATS 2020 ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabas Poczos, Jeff Schneider, Eric Xing

JMLR 2020 Contextual Explanation Networks Maruan Al-Shedivat, Avinava Dubey, Eric Xing

AISTATS 2020 Distributed, Partially Collapsed MCMC for Bayesian Nonparametrics Kumar Avinava Dubey, Michael Zhang, Eric Xing, Sinead Williamson

AISTATS 2020 Learning Sparse Nonparametric DAGs Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric Xing

ICLR 2019 AutoLoss: Learning Discrete Schedule for Alternate Optimization Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric Xing

ICMLW 2019 Every Sample a Task: Pushing the Limits of Heterogeneous Models with Personalized Regression Ben Lengerich, Bryon Aragam, Eric Xing

ICML 2019 Fault Tolerance in Iterative-Convergent Machine Learning Aurick Qiao, Bryon Aragam, Bingjing Zhang, Eric Xing

ICML 2019 Theoretically Principled Trade-Off Between Robustness and Accuracy Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric Xing, Laurent El Ghaoui, Michael Jordan

ICLR 2019 Toward Understanding the Impact of Staleness in Distributed Machine Learning Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric Xing

ECCV 2018 CIRL: Controllable Imitative Reinforcement Learning for Vision-Based Self-Driving Xiaodan Liang, Tairui Wang, Luona Yang, Eric Xing

ICML 2018 DiCE: The Infinitely Differentiable Monte Carlo Estimator Jakob Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric Xing, Shimon Whiteson

ICML 2018 Gated Path Planning Networks Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric Xing, Ruslan Salakhutdinov

ECCV 2018 Generative Semantic Manipulation with Mask-Contrasting GAN Xiaodan Liang, Hao Zhang, Liang Lin, Eric Xing

ICML 2018 Nonoverlap-Promoting Variable Selection Pengtao Xie, Hongbao Zhang, Yichen Zhu, Eric Xing

ICML 2018 Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis Pengtao Xie, Wei Wu, Yichen Zhu, Eric Xing

ECCV 2018 Real-to-Virtual Domain Unification for End-to-End Autonomous Driving Luona Yang, Xiaodan Liang, Tairui Wang, Eric Xing

ICML 2018 Transformation Autoregressive Networks Junier Oliva, Avinava Dubey, Manzil Zaheer, Barnabas Poczos, Ruslan Salakhutdinov, Eric Xing, Jeff Schneider

ICML 2017 Post-Inference Prior Swapping Willie Neiswanger, Eric Xing

ICML 2016 Diversity-Promoting Bayesian Learning of Latent Variable Models Pengtao Xie, Jun Zhu, Eric Xing

ICML 2016 Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai, Willie Neiswanger, Suvrit Sra, Eric Xing

ICML 2015 Complex Event Detection Using Semantic Saliency and Nearly-Isotonic SVM Xiaojun Chang, Yi Yang, Eric Xing, Yaoliang Yu

ICML 2015 Large-Scale Distributed Dependent Nonparametric Trees Zhiting Hu, Ho Qirong, Avinava Dubey, Eric Xing

ICML 2013 An Adaptive Learning Rate for Stochastic Variational Inference Rajesh Ranganath, Chong Wang, Blei David, Eric Xing

ICML 2013 Hierarchical Tensor Decomposition of Latent Tree Graphical Models Le Song, Mariya Ishteva, Ankur Parikh, Eric Xing, Haesun Park

ICML 2013 Markov Network Estimation from Multi-Attribute Data Mladen Kolar, Han Liu, Eric Xing

ICML 2013 Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models Sinead Williamson, Avinava Dubey, Eric Xing

AISTATS 2011 Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks Qirong Ho, Le Song, Eric Xing

AISTATS 2011 Multiscale Community Blockmodel for Network Exploration Qirong Ho, Ankur Parikh, Le Song, Eric Xing

AISTATS 2011 Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text Amr Ahmed, Qirong Ho, Choon Hui Teo, Jacob Eisenstein, Alex Smola, Eric Xing

AISTATS 2011 Online Learning of Structured Predictors with Multiple Kernels Andre Filipe Torres Martins, Noah Smith, Eric Xing, Pedro Aguiar, Mario Figueiredo

AISTATS 2010 Ultra-High Dimensional Multiple Output Learning with Simultaneous Orthogonal Matching Pursuit: Screening Approach Mladen Kolar, Eric Xing