AI RESEARCH

AgentProcessBench: Diagnosing Step-Level Process Quality in Tool-Using Agents

arXiv CS.AI

ArXi:2603.14465v1 Announce Type: new While Large Language Models (LLMs) have evolved into tool-using agents, they remain brittle in long-horizon interactions. Unlike mathematical reasoning where errors are often rectifiable via backtracking, tool-use failures frequently induce irreversible side effects, making accurate step-level verification critical. However, existing process-level benchmarks are predominantly confined to closed-world mathematical domains, failing to capture the dynamic and open-ended nature of tool execution. To bridge this gap, we