Zhang, Chiyuan

50 publications

AISTATS 2025 Balls-and-Bins Sampling for DP-SGD Lynn Chua, Badih Ghazi, Charlie Harrison, Pritish Kamath, Ravi Kumar, Ethan Jacob Leeman, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

ICML 2025 Empirical Privacy Variance Yuzheng Hu, Fan Wu, Ruicheng Xian, Yuhang Liu, Lydia Zakynthinou, Pritish Kamath, Chiyuan Zhang, David Forsyth

ICML 2025 Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards Yangsibo Huang, Milad Nasr, Anastasios Nikolas Angelopoulos, Nicholas Carlini, Wei-Lin Chiang, Christopher A. Choquette-Choo, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Ken Liu, Ion Stoica, Florian Tramèr, Chiyuan Zhang

ICLR 2025 Fantastic Copyrighted Beasts and How (Not) to Generate Them Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson

ICLRW 2025 MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities Against Hard Perturbations Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang

ICML 2025 MATH-Perturb: Benchmarking LLMs’ Math Reasoning Abilities Against Hard Perturbations Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang

ICLR 2025 MUSE: Machine Unlearning Six-Way Evaluation for Language Models Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang

NeurIPS 2025 Private Hyperparameter Tuning with Ex-Post Guarantee Badih Ghazi, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

NeurIPS 2025 Quantifying Cross-Modality Memorization in Vision-Language Models Yuxin Wen, Yangsibo Huang, Tom Goldstein, Ravi Kumar, Badih Ghazi, Chiyuan Zhang

NeurIPS 2025 Scaling Embedding Layers in Language Models Da Yu, Edith Cohen, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Daogao Liu, Chiyuan Zhang

ICML 2025 Scaling Laws for Differentially Private Language Models Ryan Mckenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang

ICLR 2025 Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang

NeurIPSW 2024 Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang

NeurIPS 2024 Evaluating Copyright Takedown Methods for Language Models Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson

ICML 2024 How Private Are DP-SGD Implementations? Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

ICLR 2024 LabelDP-Pro: Learning with Label Differential Privacy via Projections Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

COLT 2024 On Convex Optimization with Semi-Sensitive Features Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

NeurIPSW 2024 On Memorization of Large Language Models in Logical Reasoning Chulin Xie, Yangsibo Huang, Chiyuan Zhang, Da Yu, Xinyun Chen, Bill Yuchen Lin, Bo Li, Badih Ghazi, Ravi Kumar

NeurIPS 2024 Scalable DP-SGD: Shuffling vs. Poisson Subsampling Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

ICML 2023 Can Neural Network Memorization Be Localized? Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J Zico Kolter, Chiyuan Zhang

NeurIPS 2023 Counterfactual Memorization in Neural Language Models Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramer, Nicholas Carlini

ICLR 2023 Measuring Forgetting of Memorized Training Examples Matthew Jagielski, Om Thakkar, Florian Tramer, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Guha Thakurta, Nicolas Papernot, Chiyuan Zhang

ICML 2023 On User-Level Private Convex Optimization Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

NeurIPS 2023 Optimal Unbiased Randomizers for Regression with Label Differential Privacy Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V Varadarajan, Chiyuan Zhang

ICLR 2023 Quantifying Memorization Across Neural Language Models Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, Chiyuan Zhang

ICLR 2023 Regression with Label Differential Privacy Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash Varadarajan, Chiyuan Zhang

NeurIPS 2023 Sparsity-Preserving Differentially Private Training of Large Embedding Models Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

COLT 2023 Ticketed Learning–Unlearning Schemes Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang

NeurIPS 2023 User-Level Differential Privacy with Few Examples per User Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

JMLR 2022 Are All Layers Created Equal? Chiyuan Zhang, Samy Bengio, Yoram Singer

NeurIPS 2022 Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang

NeurIPS 2022 The Privacy Onion Effect: Memorization Is Relative Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramer

NeurIPS 2022 Understanding and Improving Robustness of Vision Transformers Through Patch-Based Negative Augmentation Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang

ICML 2021 Characterizing Structural Regularities of Labeled Data in Overparameterized Models Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C Mozer

NeurIPS 2021 Deep Learning with Label Differential Privacy Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

NeurIPS 2021 Do Vision Transformers See like Convolutional Neural Networks? Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy

ICML 2021 Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C Mozer

NeurIPSW 2021 Understanding and Improving Robustness of VisionTransformers Through Patch-Based NegativeAugmentation Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang

ICLR 2020 Identity Crisis: Memorization and Generalization Under Extreme Overparameterization Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer

NeurIPS 2020 What Is Being Transferred in Transfer Learning? Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang

NeurIPS 2020 What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation Vitaly Feldman, Chiyuan Zhang

ICMLW 2019 Are All Layers Created Equal? Chiyuan Zhang, Samy Bengio, Yoram Singer

ICMLW 2019 Identity Crisis: Memorization and Generalization Under Extreme Overparameterization Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer

NeurIPS 2019 Transfusion: Understanding Transfer Learning for Medical Imaging Maithra Raghu, Chiyuan Zhang, Jon Kleinberg, Samy Bengio

ICML 2018 Machine Theory of Mind Neil Rabinowitz, Frank Perbet, Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew Botvinick

ICLR 2017 Understanding Deep Learning Requires Rethinking Generalization Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals

NeurIPS 2015 Learning with a Wasserstein Loss Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio Araya, Tomaso A Poggio

JMLR 2013 Parallel Vector Field Embedding Binbin Lin, Xiaofei He, Chiyuan Zhang, Ming Ji

NeurIPS 2012 Multi-Task Vector Field Learning Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He

NeurIPS 2011 Semi-Supervised Regression via Parallel Field Regularization Binbin Lin, Chiyuan Zhang, Xiaofei He