AIBullisharXiv – CS AI · Mar 96/10
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XAI for Coding Agent Failures: Transforming Raw Execution Traces into Actionable Insights
Researchers developed an explainable AI (XAI) system that transforms raw execution traces from LLM-based coding agents into structured, human-interpretable explanations. The system enables users to identify failure root causes 2.8 times faster and propose fixes with 73% higher accuracy through domain-specific failure taxonomy, automatic annotation, and hybrid explanation generation.