Chiosa
Research collection

AI Security & Safety

Research on AI Security & Safety: explanations, evidence, limitations and connections between papers.

36 results

  1. Match an automated pass to the failure paths it tested

    A faster training recipe, a warning from a code checker, and a patch that blocks an exploit can each receive an encouraging automated result. The practical tension is whether that result covers the failure that matters for the next decision. Across these studies, a pass becomes useful when its test case and target are clear. Their checks screen settings, filter generated programs, or replay attacks, yet each leaves paths outside what it exercised. Read the pass as evidence for those tested paths.