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

• URL: http://arxiv.org/abs/2506.10086v1
• Date: Wed, 11 Jun 2025 18:06:06 GMT
• Title: Chat-of-Thought: Collaborative Multi-Agent System for Generating Domain Specific Information
• Authors: Christodoulos Constantinides, Shuxin Lin, Nianjun Zhou, Dhaval Patel,
• Abstract summary: Chat-of-Thought is designed to facilitate the generation of Failure Modes and Effects Analysis (FMEA) documents for industrial assets.<n>Chat-of-Thought employs multiple collaborative Large Language Model (LLM)-based agents with specific roles, leveraging advanced AI techniques.<n>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.
• Score: 4.771737213319029
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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