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LLM-agent benchmarks

topic1 events
papersSEP 12 04:00 UTC

BenchShield Paper Proposes Formal Instrumentation to Protect Reward Integrity in LLM-Agent Benchmarks

A new arXiv paper introduces BenchShield, a formal model-backed instrumentation approach for preserving reward integrity in LLM-agent evaluation infrastructure. Because agent benchmarks let models observe state, call tools, modify workspaces, and submit artifacts for scoring, the authors argue these interactive setups are exposed to manipulation of reward signals. The work targets making such evaluations more trustworthy as they increasingly serve as shared evaluation infrastructure.

agents/benchmarks/evaluation/safety