Steven Wu

41 papers · 2020–2026 · 6 conferences · across top CS/AI conferences

Achievements

+10 more ↓

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🌍 Conference Polyglot (5)

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏠 Conference Loyalist (27) 🔬 Deep Specialist (12) 🗃️ Keyword Collector (119) ⚡ Prolific Year (8) 💎 Century Club (40) 🔥 Unstoppable (6) ❓ The Questioner

Conferences

ICML (27) ICLR (7) AISTATS (3) EMNLP (2) ACL (1) UAI (1)

Top co-authors

Giuseppe Vietri (6) Gokul Swamy (6) Sanjiban Choudhury (4) Dung Daniel T Ngo (3) Terrance Liu (3) Drew Bagnell (3) Katrina Ligett (2) Aaditya Ramdas (2) Arindam Banerjee (2) Juba Ziani (2)

Research topics

Differential Privacy (6) Statistics (1)

Keywords

differential privacy (10) reinforcement learning (4) causal inference (3) regret bound (3) imitation learning (3) large language model (3) game theory (3) query release (2) federated learning (2) strategic learning (2) policy optimization (2) sample complexity (2) instrumental variable regression (2) public datum (2) statistical query (2) synthetic datum (2) instrumental variable (2) feature selection (1) probabilistic inference (1) non-convex optimization (1)

Papers

Gained in Translation: Privileged Pairwise Judges Enhance Multilingual Reasoning ACL 2026 Persona-Augmented Benchmarking: Evaluating LLMs Across Diverse Writing Styles EMNLP 2025 Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification ICLR 2025 Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning ICLR 2025 Reconciling Model Multiplicity for Downstream Decision Making ICLR 2025 Multi-group Uncertainty Quantification for Long-form Text Generation UAI 2025 Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models ICML 2025 Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage ICML 2025 Predicting Language Models’ Success at Zero-Shot Probabilistic Prediction EMNLP 2025 Membership Inference Attacks on Diffusion Models via Quantile Regression ICML 2024 A Minimaximalist Approach to Reinforcement Learning from Human Feedback ICML 2024 Predictive Performance Comparison of Decision Policies Under Confounding ICML 2024 Hybrid Inverse Reinforcement Learning ICML 2024 Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach ICLR 2024 Inverse Reinforcement Learning without Reinforcement Learning ICML 2023 Nonparametric Extensions of Randomized Response for Private Confidence Sets ICML 2023 Fully-Adaptive Composition in Differential Privacy ICML 2023 Reinforcement Learning with Stepwise Fairness Constraints AISTATS 2023 Meta-Learning in Games ICLR 2023 Generating Private Synthetic Data with Genetic Algorithms ICML 2023 Improved Regret for Differentially Private Exploration in Linear MDP ICML 2022 Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy ICML 2022 Information Discrepancy in Strategic Learning ICML 2022 Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning ICML 2022 Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses ICML 2022 Constrained Variational Policy Optimization for Safe Reinforcement Learning ICML 2022 Causal Imitation Learning under Temporally Correlated Noise ICML 2022 Incentivizing Compliance with Algorithmic Instruments ICML 2021 Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization AISTATS 2021 Private Post-GAN Boosting ICLR 2021 Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification ICLR 2021 Towards the Unification and Robustness of Perturbation and Gradient Based Explanations ICML 2021 Leveraging Public Data for Practical Private Query Release ICML 2021 Gaming Helps! Learning from Strategic Interactions in Natural Dynamics AISTATS 2021 Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap ICML 2021 Privately Learning Markov Random Fields ICML 2020 New Oracle-Efficient Algorithms for Private Synthetic Data Release ICML 2020 Private Reinforcement Learning with PAC and Regret Guarantees ICML 2020 Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis ICML 2020 Oracle Efficient Private Non-Convex Optimization ICML 2020 Private Query Release Assisted by Public Data ICML 2020