CharacterGLM：基于大语言模型定制中文对话AI角色
CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models
AI总结：
本文提出CharacterGLM系列模型，基于ChatGLM构建，通过配置角色属性与行为实现中文对话AI角色定制，在一致性、类人性和参与度上超越GPT等主流闭源模型，并开源6B版本及部分训练数据。
摘要：
本文介绍了CharacterGLM，这是一系列基于ChatGLM构建的模型，参数规模从6B到66B不等。我们的CharacterGLM旨在生成基于角色的对话（CharacterDial），其目标是为对话式AI系统赋予角色定制能力，以满足人们固有的社交欲望和情感需求。在CharacterGLM之上，我们可以通过配置角色的属性（身份、兴趣、观点、经历、成就、社会关系等）和行为（语言特征、情感表达、交互模式等）来定制各种AI角色或社交智能体。根据人工评估，我们的模型在一致性、类人性和参与度方面优于大多数主流闭源大语言模型，包括GPT系列。我们将发布CharacterGLM的6B版本及部分训练数据，以促进基于角色的对话生成方向的进一步研究发展。
英文摘要：
In this paper, we present CharacterGLM, a series of models built upon ChatGLM, with model sizes ranging from 6B to 66B parameters. Our CharacterGLM is designed for generating Character-based Dialogues (CharacterDial), which aims to equip a conversational AI system with character customization for satisfying people's inherent social desires and emotional needs. On top of CharacterGLM, we can customize various AI characters or social agents by configuring their attributes (identities, interests, viewpoints, experiences, achievements, social relationships, etc.) and behaviors (linguistic features, emotional expressions, interaction patterns, etc.). Our model outperforms most mainstream close-source large langauge models, including the GPT series, especially in terms of consistency, human-likeness, and engagement according to manual evaluations. We will release our 6B version of CharacterGLM and a subset of training data to facilitate further research development in the direction of character-based dialogue generation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
