Scores Alone Do Not Prove Discovery: The Discovery Certification Protocol for Auditing AI Research Agents
3.80T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2609.09219.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryProposes the Discovery Certification Protocol (DCP) for auditing AI research agents via three gates: sealed evaluation, recovery tests withholding target history, and optional truthful-feedback measurement. Controlled audits in SQLite optimization and virtual catalyst tasks produced zero recoveries across 96 episodes, bounded at 0.0468, with a deterministic LLM-free verifier.
Why it mattersConcrete auditing framework with finite-sample statistical bounds for verifying AI research agent outputs, addressing a real verification gap in agentic workflows.
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