DAUX: a Density-based Approach for Uncertainty eXplanations. - Hao Sun 017; Boris van Breugel; Jonathan Crabbé; Nabeel Seedat; Mihaela van der Schaar (CoRR, 2022)

Membership Inference Attacks against Synthetic Data through Overfitting Detection. - Boris van Breugel; Hao Sun 017; Zhaozhi Qian; Mihaela van der Schaar (AISTATS, 2023)

Neural Laplace Control for Continuous-time Delayed Systems. - Samuel Holt; Alihan Hüyük; Zhaozhi Qian; Hao Sun 017; Mihaela van der Schaar (AISTATS, 2023)

What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization. - Hao Sun 017; Boris van Breugel; Jonathan Crabbé; Nabeel Seedat; Mihaela van der Schaar (NeurIPS, 2023)

Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples. - Hao Sun 017; Alihan Hüyük; Daniel Jarrett; Mihaela van der Schaar (NeurIPS, 2023)

When is Off-Policy Evaluation Useful? A Data-Centric Perspective. - Hao Sun 017; Alex J. Chan; Nabeel Seedat; Alihan Hüyük; Mihaela van der Schaar (CoRR, 2023)

Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL. - Hao Sun 017; Alihan Hüyük; Mihaela van der Schaar (ICLR, 2024)

Dense Reward for Free in Reinforcement Learning from Human Feedback. - Alex James Chan; Hao Sun 017; Samuel Holt; Mihaela van der Schaar (ICML, 2024)

Retrieval-Augmented Thought Process as Sequential Decision Making. - Thomas Pouplin; Hao Sun 017; Samuel Holt; Mihaela van der Schaar (CoRR, 2024)

Inverse-RLignment: Inverse Reinforcement Learning from Demonstrations for LLM Alignment. - Hao Sun 017; Mihaela van der Schaar (CoRR, 2024)

Rethinking Bradley-Terry Models in Preference-Based Reward Modeling: Foundations, Theory, and Alternatives. - Hao Sun 017; Yunyi Shen; Jean-Francois Ton (CoRR, 2024)

LLMs for Generalizable Language-Conditioned Policy Learning under Minimal Data Requirements. - Thomas Pouplin; Katarzyna Kobalczyk; Hao Sun 017; Mihaela van der Schaar (CoRR, 2024)

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes. - Katarzyna Kobalczyk; Claudio Fanconi; Hao Sun 017; Mihaela van der Schaar (CoRR, 2024)

Rethinking Reward Modeling in Preference-based Large Language Model Alignment. - Hao Sun 017; Yunyi Shen; Jean-Francois Ton (ICLR, 2025)

Reviving The Classics: Active Reward Modeling in Large Language Model Alignment. - Yunyi Shen; Hao Sun 017; Jean-François Ton (CoRR, 2025)

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs. - Hao Sun 017; Yunyi Shen; Jean-Francois Ton; Mihaela van der Schaar (CoRR, 2025)

OpenReview Should be Protected and Leveraged as a Community Asset for Research in the Era of Large Language Models. - Hao Sun 017; Yunyi Shen; Mihaela van der Schaar (CoRR, 2025)

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities. - Hao Sun 017; Mihaela van der Schaar (CoRR, 2025)