| 2026 | ACL | Gained in Translation: Privileged Pairwise Judges Enhance Multilingual Reasoning. | Lintang Sutawika, Gokul Swamy, Steven Wu, Graham Neubig |
| 2025 | EMNLP | Predicting Language Models' Success at Zero-Shot Probabilistic Prediction. | Kevin Ren, Santiago Cortes-Gomez, Carlos Miguel Patio, Ananya Joshi, Ruiqi Lyu, Jingjing Tang, Alistair Turcan, Khurram Yamin, Steven Wu, Bryan Wilder |
| 2025 | EMNLP | Persona-Augmented Benchmarking: Evaluating LLMs Across Diverse Writing Styles. | Kimberly Le Truong, Riccardo Fogliato, Hoda Heidari, Steven Wu |
| 2025 | ICLR | Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification. | Santiago Cortes-Gomez, Carlos Miguel Patio, Yewon Byun, Steven Wu, Eric Horvitz, Bryan Wilder |
| 2025 | ICML | Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage. | Konstantina Bairaktari, Jiayun Wu, Steven Wu |
| 2025 | ICML | Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models. | Xiaoyu Wu, Jiaru Zhang, Steven Wu |
| 2025 | KDD | Benchmarking Fraud Detectors on Private Graph Data. | Alexander Goldberg, Giulia Fanti, Nihar B. Shah, Steven Wu |
| 2025 | UAI | Multi-group Uncertainty Quantification for Long-form Text Generation. | Terrance Liu, Steven Wu |
| 2024 | ICLR | Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach. | Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong |
| 2024 | ICML | Predictive Performance Comparison of Decision Policies Under Confounding. | Luke Guerdan, Amanda Coston, Ken Holstein, Steven Wu |
| 2024 | ICML | Hybrid Inverse Reinforcement Learning. | Juntao Ren, Gokul Swamy, Steven Wu, Drew Bagnell, Sanjiban Choudhury |
| 2024 | ICML | A Minimaximalist Approach to Reinforcement Learning from Human Feedback. | Gokul Swamy, Christoph Dann, Rahul Kidambi, Steven Wu, Alekh Agarwal |
| 2024 | ICML | Membership Inference Attacks on Diffusion Models via Quantile Regression. | Shuai Tang, Steven Wu, Sergl Aydre, Michael Kearns, Aaron Roth |
| 2023 | AISTATS | Reinforcement Learning with Stepwise Fairness Constraints. | Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David C. Parkes |
| 2023 | ICLR | Meta-Learning in Games. | Keegan Harris, Ioannis Anagnostides, Gabriele Farina, Mikhail Khodak, Steven Wu, Tuomas Sandholm |
| 2023 | ICML | Generating Private Synthetic Data with Genetic Algorithms. | Terrance Liu, Jingwu Tang, Giuseppe Vietri, Steven Wu |
| 2023 | ICML | Fully-Adaptive Composition in Differential Privacy. | Justin Whitehouse, Aaditya Ramdas, Ryan Rogers, Steven Wu |
| 2022 | ICML | Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses. | Keegan Harris, Dung Daniel T. Ngo, Logan Stapleton, Hoda Heidari, Steven Wu |
| 2022 | ICML | Improved Regret for Differentially Private Exploration in Linear MDP. | Dung Daniel T. Ngo, Giuseppe Vietri, Steven Wu |
| 2022 | ICML | Causal Imitation Learning under Temporally Correlated Noise. | Gokul Swamy, Sanjiban Choudhury, Drew Bagnell, Steven Wu |
| 2022 | ICML | Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. | Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi |
| 2021 | ICLR | Private Post-GAN Boosting. | Marcel Neunhoeffer, Steven Wu, Cynthia Dwork |
| 2021 | ICLR | Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification. | Yingxue Zhou, Steven Wu, Arindam Banerjee |
| 2021 | ICML | Towards the Unification and Robustness of Perturbation and Gradient Based Explanations. | Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Himabindu Lakkaraju |
| 2021 | ICML | Incentivizing Compliance with Algorithmic Instruments. | Dung Daniel T. Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu |
| 2021 | ICML | Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap. | Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu |