mlsanityData to 14 Oct 2026

Chat-of-Thought: Collaborative Multi-Agent System for Generating Domain Specific Information

arXiv 2506.10086 ↗First posted 11 Jun 2025cs.CLcited by 0

On the map: LLM reasoning → Reasoning for agents, planning and code

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Abstract (arXiv)

This paper presents a novel multi-agent system called Chat-of-Thought, designed to facilitate the generation of Failure Modes and Effects Analysis (FMEA) documents for industrial assets. Chat-of-Thought employs multiple collaborative Large Language Model (LLM)-based agents with specific roles, leveraging advanced AI techniques and dynamic task routing to optimize the generation and validation of FMEA tables. A key innovation in this system is the introduction of a Chat of Thought, where dynamic, multi-persona-driven discussions enable iterative refinement of content. This research explores the application domain of industrial equipment monitoring, highlights key challenges, and demonstrates the potential of Chat-of-Thought in addressing these challenges through interactive, template-driven workflows and context-aware agent collaboration.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 11 of its 23 references that are in the map. First posted on arXiv 11 Jun 2025.

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11 of 23 references.

References · 11

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