Zhang, Ce

89 publications

TMLR 2026 SiLVR: A Simple Language-Based Video Reasoning Framework Ce Zhang, Yan-Bo Lin, Ziyang Wang, Mohit Bansal, Gedas Bertasius

TMLR 2026 VScan: Rethinking Visual Token Reduction for Efficient Large Vision-Language Models Ce Zhang, Kaixin Ma, Tianqing Fang, Wenhao Yu, Hongming Zhang, Zhisong Zhang, Haitao Mi, Dong Yu

CVPR 2025 BASKET: A Large-Scale Video Dataset for Fine-Grained Skill Estimation Yulu Pan, Ce Zhang, Gedas Bertasius

ICML 2025 Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference Ce Zhang, Yixin Han, Yafei Wang, Xiaodong Yan, Linglong Kong, Ting Li, Bei Jiang

WACV 2025 Enhancing Vision-Language Few-Shot Adaptation with Negative Learning Ce Zhang, Simon Stepputtis, Katia Sycara, Yaqi Xie

ICML 2025 Improving Model Alignment Through Collective Intelligence of Open-Source Models Junlin Wang, Roy Xie, Shang Zhu, Jue Wang, Ben Athiwaratkun, Bhuwan Dhingra, Shuaiwen Leon Song, Ce Zhang, James Zou

ICLR 2025 Mixture-of-Agents Enhances Large Language Model Capabilities Junlin Wang, Jue Wang, Ben Athiwaratkun, Ce Zhang, James Zou

ICCV 2025 ONLY: One-Layer Intervention Sufficiently Mitigates Hallucinations in Large Vision-Language Models Zifu Wan, Ce Zhang, Silong Yong, Martin Q. Ma, Simon Stepputtis, Louis-Philippe Morency, Deva Ramanan, Katia Sycara, Yaqi Xie

ICLR 2025 Scaling Instruction-Tuned LLMs to Million-Token Contexts via Hierarchical Synthetic Data Generation Linda He, Jue Wang, Maurice Weber, Shang Zhu, Ben Athiwaratkun, Ce Zhang

ICLR 2025 Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Ce Zhang, Zifu Wan, Zhehan Kan, Martin Q. Ma, Simon Stepputtis, Deva Ramanan, Russ Salakhutdinov, Louis-Philippe Morency, Katia P. Sycara, Yaqi Xie

ICML 2025 Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation Jingyu Liu, Beidi Chen, Ce Zhang

ICMLW 2024 AdaNF: Quantization Group Adaptive NormalFloat for Low Bit Fine-Tuning of LLMs Yeojoon Youn, Sehoon Kim, Suhong Moon, Sang Keun Choe, Ce Zhang

ICLR 2024 AntGPT: Can Large Language Models Help Long-Term Action Anticipation from Videos? Qi Zhao, Shijie Wang, Ce Zhang, Changcheng Fu, Minh Quan Do, Nakul Agarwal, Kwonjoon Lee, Chen Sun

AAAI 2024 Concept-Guided Prompt Learning for Generalization in Vision-Language Models Yi Zhang, Ce Zhang, Ke Yu, Yushun Tang, Zhihai He

DMLR 2024 DMLR: Data-Centric Machine Learning Research - Past, Present and Future Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William A Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlaš, Ahmed Alaa, Adji Bousso Dieng, Natasha Noy, Vijay Janapa Reddi, James Zou, Praveen Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson

ICLR 2024 Data Debugging with Shapley Importance over Machine Learning Pipelines Bojan Karlaš, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang

NeurIPS 2024 Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models Ce Zhang, Simon Stepputtis, Katia Sycara, Yaqi Xie

ICLR 2024 Effective and Efficient Federated Tree Learning on Hybrid Data Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song

NeurIPS 2024 FM-Delta: Lossless Compression for Storing Massive Fine-Tuned Foundation Models Wanyi Ning, Jingyu Wang, Qi Qi, Mengde Zhu, Haifeng Sun, Daixuan Cheng, Jianxin Liao, Ce Zhang

CVPR 2024 HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation Ce Zhang, Simon Stepputtis, Joseph Campbell, Katia Sycara, Yaqi Xie

NeurIPSW 2024 Incorporating Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Ce Zhang, Zifu Wan, Zhehan Kan, Martin Q. Ma, Simon Stepputtis, Deva Ramanan, Russ Salakhutdinov, Louis-Philippe Morency, Katia P. Sycara, Yaqi Xie

WACV 2024 Learning to Adapt CLIP for Few-Shot Monocular Depth Estimation Xueting Hu, Ce Zhang, Yi Zhang, Bowen Hai, Ke Yu, Zhihai He

ICML 2024 Mechanistic Design and Scaling of Hybrid Architectures Michael Poli, Armin W Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Re, Ce Zhang, Stefano Massaroli

NeurIPS 2024 OAM-TCD: A Globally Diverse Dataset of High-Resolution Tree Cover Maps Josh Veitch-Michaelis, Andrew Cottam, Daniella Schweizer, Eben N. Broadbent, David Dao, Ce Zhang, Angelica Almeyda Zambrano, Simeon Max

WACV 2024 Object-Centric Video Representation for Long-Term Action Anticipation Ce Zhang, Changcheng Fu, Shijie Wang, Nakul Agarwal, Kwonjoon Lee, Chiho Choi, Chen Sun

MLOSS 2024 OpenBox: A Python Toolkit for Generalized Black-Box Optimization Huaijun Jiang, Yu Shen, Yang Li, Beicheng Xu, Sixian Du, Wentao Zhang, Ce Zhang, Bin Cui

NeurIPS 2024 RedPajama: An Open Dataset for Training Large Language Models Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang

ICMLW 2024 Test-Time Prototype Evolution for Generalizable Vision-Language Models Ce Zhang, Simon Stepputtis, Katia P. Sycara, Yaqi Xie

ICML 2023 CocktailSGD: Fine-Tuning Foundation Models over 500Mbps Networks Jue Wang, Yucheng Lu, Binhang Yuan, Beidi Chen, Percy Liang, Christopher De Sa, Christopher Re, Ce Zhang

ICLR 2023 Contrastive Learning for Unsupervised Domain Adaptation of Time Series Yilmazcan Ozyurt, Stefan Feuerriegel, Ce Zhang

NeurIPS 2023 DataPerf: Benchmarks for Data-Centric AI Development Mark Mazumder, Colby Banbury, Xiaozhe Yao, Bojan Karlaš, William Gaviria Rojas, Sudnya Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen Paritosh, Ce Zhang, James Y Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi

ICML 2023 Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Re, Beidi Chen

ICML 2023 FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li

ICML 2023 FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Re, Ion Stoica, Ce Zhang

ICMLW 2023 GPT-Zip: Deep Compression of Finetuned Large Language Models Berivan Isik, Hermann Kumbong, Wanyi Ning, Xiaozhe Yao, Sanmi Koyejo, Ce Zhang

NeurIPS 2023 Goal-Conditioned Predictive Coding for Offline Reinforcement Learning Zilai Zeng, Ce Zhang, Shijie Wang, Chen Sun

NeurIPSW 2023 Goal-Conditioned Predictive Coding for Offline Reinforcement Learning Zilai Zeng, Ce Zhang, Shijie Wang, Chen Sun

TMLR 2023 Holistic Evaluation of Language Models Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D Manning, Christopher Re, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Andrew Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

NeurIPS 2023 Laughing Hyena Distillery: Extracting Compact Recurrences from Convolutions Stefano Massaroli, Michael Poli, Dan Fu, Hermann Kumbong, Rom Parnichkun, David Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio

CVPRW 2023 MotionTrack: End-to-End Transformer-Based Multi-Object Tracking with LiDAR-Camera Fusion Ce Zhang, Chengjie Zhang, Yiluan Guo, Lingji Chen, Michael Happold

CVPR 2023 Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation Yushun Tang, Ce Zhang, Heng Xu, Shuoshuo Chen, Jie Cheng, Luziwei Leng, Qinghai Guo, Zhihai He

NeurIPSW 2023 Robust Hierarchical Scene Graph Generation Ce Zhang, Simon Stepputtis, Joseph Campbell, Katia Sycara, Yaqi Xie

CVPR 2023 Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation Zhehan Kan, Shuoshuo Chen, Ce Zhang, Yushun Tang, Zhihai He

NeurIPS 2023 Skill-It! a Data-Driven Skills Framework for Understanding and Training Language Models Mayee Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré

NeurIPS 2023 WordScape: A Pipeline to Extract Multilingual, Visually Rich Documents with Layout Annotations from Web Crawl Data Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian Foster, Bo Li, Rick Stevens, Ce Zhang

ICML 2022 Certifying Out-of-Domain Generalization for Blackbox Functions Maurice G Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang

NeurIPS 2022 Certifying Some Distributional Fairness with Subpopulation Decomposition Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li

NeurIPS 2022 Decentralized Training of Foundation Models in Heterogeneous Environments Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang

NeurIPS 2022 Fine-Tuning Language Models over Slow Networks Using Activation Quantization with Guarantees Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang

LoG 2022 GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks Kenza Amara, Zhitao Ying, Zitao Zhang, Zhichao Han, Yang Zhao, Yinan Shan, Ulrik Brandes, Sebastian Schemm, Ce Zhang

NeurIPS 2022 Improving Certified Robustness via Statistical Learning with Logical Reasoning Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlaš, Ji Liu, Heng Guo, Ce Zhang, Bo Li

NeurIPSW 2022 Improving Vertical Federated Learning by Efficient Communication with ADMM Chulin Xie, Pin-Yu Chen, Ce Zhang, Bo Li

ICLR 2022 Neural Methods for Logical Reasoning over Knowledge Graphs Alfonso Amayuelas, Shuai Zhang, Xi Susie Rao, Ce Zhang

ECCVW 2022 Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation Yangheng Zhao, Jun Wang, Xiaolong Li, Yue Hu, Ce Zhang, Yanfeng Wang, Siheng Chen

AAAI 2022 ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Kenza Amara, Attila Steinegger, Ce Zhang, Xiaoxiang Zhu

AAAI 2022 TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets Susie Xi Rao, Johannes Rausch, Peter H. Egger, Ce Zhang

NeurIPS 2022 VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang

CVPR 2022 Which Model to Transfer? Finding the Needle in the Growing Haystack Cedric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lučić

ICLR 2022 iFlood: A Stable and Effective Regularizer Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding

AISTATS 2021 Online Active Model Selection for Pre-Trained Classifiers Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlaš, Johannes Rausch, Ce Zhang, Andreas Krause

ICML 2021 1-Bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He

AAAI 2021 DocParser: Hierarchical Document Structure Parsing from Renderings Johannes Rausch, Octavio Martinez, Fabian Bissig, Ce Zhang, Stefan Feuerriegel

ICML 2021 Evolving Attention with Residual Convolutions Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong

ICML 2021 Knowledge Enhanced Machine Learning Pipeline Against Diverse Adversarial Attacks Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li

AAAI 2021 MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements Yang Li, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang, Bin Cui

CVPR 2021 Scalability vs. Utility: Do We Have to Sacrifice One for the Other in Data Importance Quantification? Ruoxi Jia, Fan Wu, Xuehui Sun, Jiacen Xu, David Dao, Bhavya Kailkhura, Ce Zhang, Bo Li, Dawn Song

NeurIPS 2021 TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin I. Rubinstein, Ce Zhang, Bo Li

ICML 2020 Don’t Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui

AAAI 2020 Efficient Automatic CASH via Rising Bandits Yang Li, Jiawei Jiang, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui

NeurIPS 2020 Learning to Mutate with Hypergradient Guided Population Zhiqiang Tao, Yaliang Li, Bolin Ding, Ce Zhang, Jingren Zhou, Yun Fu

NeurIPS 2020 On Convergence of Nearest Neighbor Classifiers over Feature Transformations Luka Rimanic, Cedric Renggli, Bo Li, Ce Zhang

NeurIPS 2020 Spectral Temporal Graph Neural Network for Multivariate Time-Series Forecasting Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Congrui Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang

AAAI 2020 TextNAS: A Neural Architecture Search Space Tailored for Text Representation Yujing Wang, Yaming Yang, Yiren Chen, Jing Bai, Ce Zhang, Guinan Su, Xiaoyu Kou, Yunhai Tong, Mao Yang, Lidong Zhou

AAAI 2020 Topic Modeling on Document Networks with Adjacent-Encoder Ce Zhang, Hady W. Lauw

AISTATS 2019 AutoML from Service Provider’s Perspective: Multi-Device, Multi-Tenant Model Selection with GP-EI Chen Yu, Bojan Karlaš, Jie Zhong, Ce Zhang, Ji Liu

ICML 2019 DL2: Training and Querying Neural Networks with Logic Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin Vechev

ICML 2019 Distributed Learning over Unreliable Networks Chen Yu, Hanlin Tang, Cedric Renggli, Simon Kassing, Ankit Singla, Dan Alistarh, Ce Zhang, Ji Liu

AISTATS 2019 Towards Efficient Data Valuation Based on the Shapley Value Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos

ICML 2018 $d^2$: Decentralized Training over Decentralized Data Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu

ICML 2018 Asynchronous Decentralized Parallel Stochastic Gradient Descent Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu

NeurIPS 2018 Communication Compression for Decentralized Training Hanlin Tang, Shaoduo Gan, Ce Zhang, Tong Zhang, Ji Liu

AISTATS 2018 Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond Heng Guo, Kaan Kara, Ce Zhang

NeurIPS 2017 Can Decentralized Algorithms Outperform Centralized Algorithms? a Case Study for Decentralized Parallel Stochastic Gradient Descent Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu

ICML 2017 ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang

NeurIPS 2016 Cyclades: Conflict-Free Asynchronous Machine Learning Xinghao Pan, Maximilian Lam, Stephen Tu, Dimitris Papailiopoulos, Ce Zhang, Michael I Jordan, Kannan Ramchandran, Christopher Ré

NeurIPS 2015 Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width Christopher M De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré

NeurIPS 2015 Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms Christopher M De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré, Christopher Ré

NeurIPS 2014 Parallel Feature Selection Inspired by Group Testing Yingbo Zhou, Utkarsh Porwal, Ce Zhang, Hung Q Ngo, Xuanlong Nguyen, Christopher Ré, Venu Govindaraju

NeurIPS 2013 An Approximate, Efficient LP Solver for LP Rounding Srikrishna Sridhar, Stephen Wright, Christopher Re, Ji Liu, Victor Bittorf, Ce Zhang