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Autores principales: Bai, Ting, Kang, Jiazheng, Fan, Jiayang
Formato: Preprint
Publicado: 2024
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Acceso en línea:https://arxiv.org/abs/2412.20024
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author Bai, Ting
Kang, Jiazheng
Fan, Jiayang
author_facet Bai, Ting
Kang, Jiazheng
Fan, Jiayang
contents We introduce a comprehensive large-scale role-playing agent corpus, termed BaiJia, that comprises various Chinese historical characters. This corpus is noteworthy for being the pioneering compilation of low-resource data that can be utilized in large language models (LLMs) to engage in AI-driven historical role-playing agents. BaiJia addresses the challenges in terms of fragmented historical textual records in different forms and modalities, integrating various characters' information, including their biographical, literary, family relations, historical events, and so on. We conduct extensive experiments to demonstrate the effectiveness of our BaiJia agent corpus in bolstering the role-playing abilities of various foundational LLMs, and promoting the development and assessment of LLMs in the context of historical role-playing tasks. The agent corpus is available at baijia.online.
format Preprint
id arxiv_https___arxiv_org_abs_2412_20024
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle BaiJia: A Large-Scale Role-Playing Agent Corpus of Chinese Historical Characters
Bai, Ting
Kang, Jiazheng
Fan, Jiayang
Artificial Intelligence
Computation and Language
We introduce a comprehensive large-scale role-playing agent corpus, termed BaiJia, that comprises various Chinese historical characters. This corpus is noteworthy for being the pioneering compilation of low-resource data that can be utilized in large language models (LLMs) to engage in AI-driven historical role-playing agents. BaiJia addresses the challenges in terms of fragmented historical textual records in different forms and modalities, integrating various characters' information, including their biographical, literary, family relations, historical events, and so on. We conduct extensive experiments to demonstrate the effectiveness of our BaiJia agent corpus in bolstering the role-playing abilities of various foundational LLMs, and promoting the development and assessment of LLMs in the context of historical role-playing tasks. The agent corpus is available at baijia.online.
title BaiJia: A Large-Scale Role-Playing Agent Corpus of Chinese Historical Characters
topic Artificial Intelligence
Computation and Language
url https://arxiv.org/abs/2412.20024