构建首个中文历史角色扮演大模型语料库，助力AI演活历史人物。
BaiJia: A Large-Scale Role-Playing Agent Corpus of Chinese Historical Characters
- 整合多源历史文本，构建包含人物生平、关系、事件的中文历史角色语料库。
- 在多个基础大模型上验证，显著提升角色扮演能力，推动历史对话评估发展。
- 适合历史教育、AI角色创作与中文大模型评测研究者使用。
我们提出一个全面的大规模角色扮演智能体语料库BaiJia，涵盖多种中国历史人物。该语料库是首个面向低资源数据的综合性编纂，可被大语言模型（LLMs）用于驱动历史角色扮演智能体。针对历史文本记录分散、形式多样等问题，BaiJia融合了人物传记、文学作品、家族关系及历史事件等多维度信息。通过大量实验，验证了BaiJia在增强各类基础大模型角色扮演能力方面的有效性，并推动了大模型在历史角色扮演任务中的发展与评估。语料库可访问：baijia.online。
原文摘要 · Abstract (English)
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.
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