PRO-Step: Step-level Process Reward Optimization for Retrieval-Augmented Generation
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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 propagation, where early retrieval failures confound subsequent steps. Standard outcome-bas…
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- 2026-09-03 04:00 · arXiv cs.CL
PRO-Step: Step-level Process Reward Optimization for Retrieval-Augmented Generation