作者位次 #3/6ACL 2026Poster· Natural Language Processing
W ild R eward: Learning Reward Models from In-the-Wild Human Interactions
Hao Peng · Yunjia Qi · Xiaozhi Wang · Zijun Yao · Lei Hou · Juanzi Li
摘要
Reward models (RMs) are crucial for the training of large language models (LLMs), yet they typically rely on large-scale human-annotated preference pairs. With the widespread deployment of LLMs, in-the-wild interactions have emerged as a rich source of implicit reward signals. This raises the que...