PRO-Step: Step-level Process Reward Optimization for Retrieval-Augmented Generation
Read the original at arxiv.org→arXiv:2609.01658v1 Announce Type: new Abstract: Retrieval-Augmented Generation enhances Large Language Models by grounding responses in external knowledge, but multi-hop reasoning remains vulnerable to error...
Coverage timeline
- Sep 3, 04:00 UTC arXiv cs.CL lead source PRO-Step: Step-level Process Reward Optimization for Retrieval-Augmented Generation