arXiv Machine Learning
Offline Constrained RLHF with Multiple Preference Oracles
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Efficient Exploration for Iterative Nash Preference Optimization
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Learning-Based Stochastic Optimal Control with Infinite-Horizon Probabilistic Constraints
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Learning Fair Pareto-Optimal Policies in Multi-Objective Reinforcement Learning
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Multi-Objective Preference Optimization: Improving Human Alignment of Generative Models
arXiv:2505. 10892v2 Announce Type: replace Abstract: Post-training LLMs with RLHF and preference optimization methods (e.
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Transductive Off-policy Proximal Policy Optimization
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