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Autor principal: Rasal, Sumedh
Formato: Preprint
Publicado: 2024
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Acceso en línea:https://arxiv.org/abs/2401.01312
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author Rasal, Sumedh
author_facet Rasal, Sumedh
contents Large Language Models (LLMs) have revolutionized Natural Language Processing but exhibit limitations, particularly in autonomously addressing novel challenges such as reasoning and problem-solving. Traditional techniques like chain-of-thought prompting necessitate explicit human guidance. This paper introduces a novel multi-agent communication framework, inspired by the CAMEL model, to enhance LLMs' autonomous problem-solving capabilities. The framework employs multiple LLM agents, each with a distinct persona, engaged in role-playing communication, offering a nuanced and adaptable approach to diverse problem scenarios. Extensive experimentation demonstrates the framework's superior performance and adaptability, providing valuable insights into the collaborative potential of multiple agents in overcoming the limitations of individual models.
format Preprint
id arxiv_https___arxiv_org_abs_2401_01312
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle LLM Harmony: Multi-Agent Communication for Problem Solving
Rasal, Sumedh
Multiagent Systems
Large Language Models (LLMs) have revolutionized Natural Language Processing but exhibit limitations, particularly in autonomously addressing novel challenges such as reasoning and problem-solving. Traditional techniques like chain-of-thought prompting necessitate explicit human guidance. This paper introduces a novel multi-agent communication framework, inspired by the CAMEL model, to enhance LLMs' autonomous problem-solving capabilities. The framework employs multiple LLM agents, each with a distinct persona, engaged in role-playing communication, offering a nuanced and adaptable approach to diverse problem scenarios. Extensive experimentation demonstrates the framework's superior performance and adaptability, providing valuable insights into the collaborative potential of multiple agents in overcoming the limitations of individual models.
title LLM Harmony: Multi-Agent Communication for Problem Solving
topic Multiagent Systems
url https://arxiv.org/abs/2401.01312