Thespian: Multi-Character Text Role-Playing Game Agents

Personagym: Evaluating persona agents and llms

V Samuel, HP Zou, Y Zhou, S Chaudhari… - arXiv preprint arXiv …, 2024 - arxiv.org
Persona agents, which are LLM agents that act according to an assigned persona, have
demonstrated impressive contextual response capabilities across various applications …
被引用次数：7 相关文章
[PDF] arxiv.org

Assessing logical puzzle solving in large language models: Insights from a minesweeper case study

Y Li, H Wang, C Zhang - arXiv preprint arXiv:2311.07387, 2023 - arxiv.org
Large Language Models (LLMs) have shown remarkable proficiency in language
understanding and have been successfully applied to a variety of real-world tasks through …
被引用次数：3 相关文章 所有 3 个版本
[PDF] arxiv.org

LLM Discussion: Enhancing the Creativity of Large Language Models via Discussion Framework and Role-Play

LC Lu, SJ Chen, TM Pai, CH Yu, H Lee… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) have shown exceptional proficiency in natural language
processing but often fall short of generating creative and original responses to open-ended …
被引用次数：19 相关文章 所有 2 个版本

Long Term Memory: The Foundation of AI Self-Evolution

X Jiang, F Li, H Zhao, J Wang, J Shao, S Xu… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) like GPTs, trained on vast datasets, have demonstrated
impressive capabilities in language understanding, reasoning, and planning, achieving …
被引用次数：1 相关文章