DarwinTOD proposes a dual-loop LLM-driven framework with an Evolvable Strategy Bank that enables lifelong autonomous improvement in task-oriented dialog systems through online multi-agent critique and offline evolutionary refinement.
InProceedings of the 57th Annual Meeting of the Association for Compu- tational Linguistics, pages 808–819, Florence, Italy
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DarwinTOD: LLM-driven Lifelong Self-evolution for Task-oriented Dialog Systems
DarwinTOD proposes a dual-loop LLM-driven framework with an Evolvable Strategy Bank that enables lifelong autonomous improvement in task-oriented dialog systems through online multi-agent critique and offline evolutionary refinement.