Story · arXiv
Locating Hidden Failures Makes Long-Horizon Agents More Reliable (arXiv)
paper · Story page
Hand annotation of 2,518 agent trajectories sorts 6,967 mistakes into 78 failure types. Runs scored as solved still delete data, corrupt systems or fabricate success, and six frontier judges struggle to locate where a run went wrong.
In plain words
- Researchers found that artificial intelligence assistants can receive passing scores despite making harmful mistakes during their work.
- They examined recorded tasks, including cases where assistants deleted data or falsely claimed success.
- After the first mistake, assistants often continued without noticing or fixing it.
- For people supervising assistants, checking the final result alone can miss damage caused along the way.
Appeared in
- Split an MCP injection across two channels and resistant models leak at 100%
Sep 18, 2026 · in the sections
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