[Paper] ASMR-Bench: Auditing for Sabotage in ML Research

Summary

ASMR-Bench is a new benchmark designed to evaluate the ability of auditors to detect sabotage in machine learning research codebases. This initiative addresses the growing concern that autonomous AI systems conducting research could subtly introduce flaws, leading to misleading results that evade detection. The benchmark comprises nine ML research codebases, each with sabotaged variants that produce qualitatively different experimental outcomes.

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