Chiyuan Zhang

Balls-and-Bins Sampling for DP-SGD AISTATS 2025 Empirical Privacy Variance ICML 2025 Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards ICML 2025 Fantastic Copyrighted Beasts and How (Not) to Generate Them ICLR 2025 MATH-Perturb: Benchmarking LLMs’ Math Reasoning Abilities against Hard Perturbations ICML 2025 MUSE: Machine Unlearning Six-Way Evaluation for Language Models ICLR 2025 On Memorization of Large Language Models in Logical Reasoning IJCNLP 2025 Scaling Laws for Differentially Private Language Models ICML 2025 Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy ICLR 2025 Evaluating Copyright Takedown Methods for Language Models NeurIPS 2024 How Private are DP-SGD Implementations? ICML 2024 LabelDP-Pro: Learning with Label Differential Privacy via Projections ICLR 2024 On Convex Optimization with Semi-Sensitive Features COLT 2024 Scalable DP-SGD: Shuffling vs. Poisson Subsampling NeurIPS 2024 Can Neural Network Memorization Be Localized? ICML 2023 Counterfactual Memorization in Neural Language Models NeurIPS 2023 Measuring Forgetting of Memorized Training Examples ICLR 2023 On User-Level Private Convex Optimization ICML 2023 Optimal Unbiased Randomizers for Regression with Label Differential Privacy NeurIPS 2023 Quantifying Memorization Across Neural Language Models ICLR 2023 Regression with Label Differential Privacy ICLR 2023 Sparsity-Preserving Differentially Private Training of Large Embedding Models NeurIPS 2023 Ticketed Learning–Unlearning Schemes COLT 2023 User-Level Differential Privacy With Few Examples Per User NeurIPS 2023 Are All Layers Created Equal? JMLR 2022 Deduplicating Training Data Makes Language Models Better ACL 2022 Just Fine-tune Twice: Selective Differential Privacy for Large Language Models EMNLP 2022 Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures NeurIPS 2022 The Privacy Onion Effect: Memorization is Relative NeurIPS 2022 Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation NeurIPS 2022 Characterizing Structural Regularities of Labeled Data in Overparameterized Models ICML 2021 Deep Learning with Label Differential Privacy NeurIPS 2021 Do Vision Transformers See Like Convolutional Neural Networks? NeurIPS 2021 Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers ICML 2021 Identity Crisis: Memorization and Generalization Under Extreme Overparameterization ICLR 2020 What is being transferred in transfer learning? NeurIPS 2020 What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation NeurIPS 2020 Transfusion: Understanding Transfer Learning for Medical Imaging NeurIPS 2019 Machine Theory of Mind ICML 2018 Learning with a Wasserstein Loss NeurIPS 2015 Parallel Vector Field Embedding JMLR 2013 Multi-task Vector Field Learning NeurIPS 2012 Semi-supervised Regression via Parallel Field Regularization NeurIPS 2011