Who Guards the Benchmarks? Automated Auditing of LLM Agent Benchmarks
Quick summary
arXiv:2604.24955v2 Announce Type: replace-cross Abstract: As benchmarks grow in complexity, many apparent agent failures are not failures of the agent at all---they are failures of the benchmark itself: broken specifications, implicit assumptions, and rigid evaluation scripts that penalize valid alternative approaches. We propose employing frontier LLMs as systematic auditors of evaluation infrastructure, and realize this vision through BenchGuard, the first framework explicitly designed for joint cross-artifact auditing of execution-based agent benchmarks. BenchGuard cross-verifies all benchm
Key takeaways
- arXiv:2604.24955v2 Announce Type: replace-cross Abstract: As benchmarks grow in complexity, many apparent agent failures are not failures of the agent at all---they are failures of the benchmark itself: broken specifications, implicit assumptions, and rigid evaluation scripts that penalize valid alternative approaches.
- We propose employing frontier LLMs as systematic auditors of evaluation infrastructure, and realize this vision through BenchGuard, the first framework explicitly designed for joint cross-artifact auditing of execution-based agent benchmarks.
- BenchGuard cross-verifies all benchm
Why it matters
AI progress is not only a software story. Chips, data centers and energy decisions help determine which models can operate economically and what end users ultimately pay.
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