Explaining AI Agents Through Execution Traces
This work presents a post-hoc XAI framework that transforms a lengthy agent's execution trace into a structured report and a faithful natural-language explanation explicitly grounded in its observable behavior, outperforming naive LLM-generated explanations.
Vittoria Vineis, Fabiano Veglianti, Lorenzo Antonelli et al.
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