Feb. 27, 2024, 5:44 a.m. | Jintian Zhang, Xin Xu, Ningyu Zhang, Ruibo Liu, Bryan Hooi, Shumin Deng

cs.LG updates on arXiv.org arxiv.org

arXiv:2310.02124v2 Announce Type: replace-cross
Abstract: As Natural Language Processing (NLP) systems are increasingly employed in intricate social environments, a pressing query emerges: Can these NLP systems mirror human-esque collaborative intelligence, in a multi-agent society consisting of multiple large language models (LLMs)? This paper probes the collaboration mechanisms among contemporary NLP systems by melding practical experiments with theoretical insights. We fabricate four unique `societies' comprised of LLM agents, where each agent is characterized by a specific `trait' (easy-going or overconfident) and …

agents arxiv collaboration cs.ai cs.cl cs.cy cs.lg cs.ma llm psychology social type view

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