3 papers
cs.CL2026
Fast-Slow Thinking RM: Efficient Integration of Scalar and Generative Reward Models
Jiayun Wu, Peixu Hou, Shan Qu +3
Reward models (RMs) are critical for aligning Large Language Models via Reinforcement Learning from Human Feedback (RLHF). While Generative Reward Models (GRMs) achieve superior ac…
cs.HC2026
Power Echoes: Investigating Moderation Biases in Online Power-Asymmetric Conflicts
Yaqiong Li, Peng Zhang, Peixu Hou +7
Online power-asymmetric conflicts are prevalent, and most platforms rely on human moderators to conduct moderation currently. Previous studies have been continuously focusing on in…
cs.AI2026
A Curriculum Learning Approach to Reinforcement Learning: Leveraging RAG for Multimodal Question Answering
Chenliang Zhang, Lin Wang, Yuanyuan Lu +4
This paper describes the solutions of the Dianping-Trust-Safety team for the META CRAG-MM challenge. The challenge requires building a comprehensive retrieval-augmented generation…