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← Authors

Zhun Deng

23 papers · 2020–2025 · 6 conferences · across top CS/AI conferences

Achievements

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+10 more ↓ 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (16) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6)
πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown πŸ’Ž Century Club (23) πŸ”₯ Unstoppable (6) ⚑ Prolific Year (8) ❓ The Questioner (2) πŸ—ƒοΈ Keyword Collector (78)

Conferences

ICML (9) ICLR (6) AISTATS (3) NIPS (3) ACL (1) JMLR (1)

Top co-authors

Linjun Zhang (10) James Zou (7) Kenji Kawaguchi (6) Toniann Pitassi (3) Wenlong Ji (3) Thomas P Zollo (3) Jiaoyang Huang (3) Jake Snell (3) Richard Zemel (3) David Madras (2)

Keywords

adversarial training (3) semi-supervised learning (3) representation learning (3) domain adaptation (2) adversarial robustness (2) generalization bound (2) neural network (2) data augmentation (2) contrastive learning (2) information bottleneck (1) transfer learning (1) feature learning (1) policy optimization (1) uncertainty quantification (1) risk management (1) robust optimization (1) preference alignment (1) knowledge transfer (1) self-supervised learning (1) sequential decision making (1)

Papers

Conformal Tail Risk Control for Large Language Model Alignment ICML 2025 Synergistic Weak-Strong Collaboration by Aligning Preferences ACL 2025 QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions ICML 2025 Learning and Forgetting Unsafe Examples in Large Language Models ICML 2024 Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models ICLR 2024 Analyzing and Mitigating Object Hallucination in Large Vision-Language Models ICLR 2024 FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data ICLR 2023 The Power of Contrast for Feature Learning: A Theoretical Analysis JMLR 2023 PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification NIPS 2023 Distribution-Free Statistical Dispersion Control for Societal Applications NIPS 2023 Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data AISTATS 2023 Reinforcement Learning with Stepwise Fairness Constraints AISTATS 2023 Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions ICLR 2023 How Does Information Bottleneck Help Deep Learning? ICML 2023 When and How Mixup Improves Calibration ICML 2022 Robustness Implies Generalization via Data-Dependent Generalization Bounds ICML 2022 An Unconstrained Layer-Peeled Perspective on Neural Collapse ICLR 2022 Improving Adversarial Robustness via Unlabeled Out-of-Domain Data AISTATS 2021 Adversarial Training Helps Transfer Learning via Better Representations NIPS 2021 Toward Better Generalization Bounds with Locally Elastic Stability ICML 2021 How Does Mixup Help With Robustness and Generalization? ICLR 2021 Interpreting Robust Optimization via Adversarial Influence Functions ICML 2020 Towards Understanding the Dynamics of the First-Order Adversaries ICML 2020