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Preference-based Reinforcement Learning

3 papers across 3 sessions

Poster Session 2

1 paper
Wednesday, December 3, 2025 · 4:30 PM → 7:30 PM
Exhibit Hall C,D,E
PRIMT: Preference-based Reinforcement Learning with Multimodal Feedback and Trajectory Synthesis from Foundation Models
#2209 · Ruiqi Wang, Dezhong Zhao, Ziqin Yuan, Tianyu Shao, Guohua Chen, Dominic Kao, Sungeun Hong, Byung-Cheol Min

Poster Session 4

1 paper
Thursday, December 4, 2025 · 4:30 PM → 7:30 PM
Exhibit Hall C,D,E
Preference-based Reinforcement Learning beyond Pairwise Comparisons: Benefits of Multiple Options
#3310 · Joongkyu Lee, Seouh-won Yi, Min-hwan Oh

We present the first theoretical analysis of PbRL with ranking feedback, showing that longer ranking feedback can provably improve sample efficiency.

Poster Session 6

1 paper
Friday, December 5, 2025 · 4:30 PM → 7:30 PM
Exhibit Hall C,D,E
Uncertainty-aware Preference Alignment for Diffusion Policies
#508 · Runqing Miao, Sheng Xu, Runyi Zhao, Wai Kin (Victor) Chan, Guiliang Liu

We propose Diff-UAPA, a novel framework that aligns diffusion policies with human preferences by integrating uncertainty-aware objectives and MAP estimation.