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arXiv — cs.AI preprintsInternational2 October 2026

DeFA: Dependency-Guided Failure Attribution for LLM Agents

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arXiv:2610.01256v1 Announce Type: new Abstract: Errors in LLM agent executions and their visible consequences can be separated by many steps, making decisive-error localization a matter of understanding both step content and step dependencies. We introduce DeFA, a dependency-guided framework for agent failure attribution. DeFA first combines protocol relations and semantic dependencies into an event dependency graph spanning the trajectory. It then identifies events that may violate task requirements and traces their sources and subsequent effects to construct a failure propagation graph. Fina
— arXiv — cs.AI preprints

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