The Necessity of a Unified Framework for LLM-Based Agent Evaluation

ArXi:2602.03238v2 Announce Type: replace With the advent of Large Language Models (LLMs), general-purpose agents have seen fundamental advancements. However, evaluating these agents presents unique challenges that distinguish them from static QA benchmarks. We observe that current agent benchmarks are heavily confounded by extraneous factors, including system prompts, toolset configurations, and environmental dynamics.