PAWS: Preference Learning with Advantage-Weighted Segments
Published in ICML 2026, 2026
A preference-based RL method that aligns utility training with policy optimization using segment-level advantage functions.
Recommended citation: Aleksandar Taranovic, Onur Celik, Niklas Freymuth, Ge Li, Serge Thilges, Huy Le, Tai Hoang, Rania Rayyes, Gerhard Neumann. (2026). "PAWS: Preference Learning with Advantage-Weighted Segments." International Conference on Machine Learning (ICML).
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