AI RESEARCH
Process Reward Agents for Steering Knowledge-Intensive Reasoning
arXiv CS.AI
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ArXi:2604.09482v1 Announce Type: new Reasoning in knowledge-intensive domains remains challenging as intermediate steps are often not locally verifiable: unlike math or code, evaluating step correctness may require synthesizing clues across large external knowledge sources. As a result, subtle errors can propagate through reasoning traces, potentially never to be detected.