Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures
How researchers are turning AI failure diagnostics into a high-efficiency search operation
The increasing deployment of AI agents in long-horizon tasks yields massive execution logs. Diagnosing failures within these records is crucial for reliability, as it transforms outcome-level signals into actionable interventions. The sheer scale of the data renders human review ...
ArXiv CS.AI
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As AI agents increasingly handle complex, multi-step workflows, the ability to pinpoint the exact moment of failure within massive log datasets becomes a critical bottleneck for system reliability. This research transforms opaque error signals into actionable diagnostics, paving the way for more autonomous and self-correcting agent architectures.
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