3 papers
cs.LG2026
Good Reasoning Makes Good Demonstrations: Implicit Reasoning Quality Supervision via In-Context Reinforcement Learning
Tiehua Mei, Minxuan Lv, Leiyu Pan +5
Reinforcement Learning with Verifiable Rewards (RLVR) improves reasoning in large language models but treats all correct solutions equally, potentially reinforcing flawed traces th…
cs.LG2026
ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation
Hongru Hou, Tiehua Mei, Denghui Geng +5
Proactive Recommender Systems (PRSs) aim to guide user preference shift toward target items by generating paths of intermediate recommendations. Reinforcement learning (RL) provide…
cs.LG2026
Distance-Matrix Wasserstein Statistics for Scalable Gromov--Wasserstein Learning
Ao Xu, Tieru Wu
Gromov--Wasserstein (GW) distances compare graphs, shapes, and point clouds through internal distances, without requiring a common coordinate system. This invariance is powerful, b…