探索大型语言模型模拟人格的潜力
Exploring the Potential of Large Language Models to Simulate Personality
AI总结：
本文针对对话式AI的人格化挑战，利用大型语言模型（LLMs）基于大五人格模型模拟人格特质，提出含预定义人格特征的生成文本数据集及分析框架，测试模型人格模拟能力。
摘要：
随着大型语言模型（LLMs）的发展，对话式人工智能的研究重点已从仅生成连贯且相关的响应转向应对更复杂的挑战，例如个性化对话系统。为了提高用户参与度，聊天机器人通常被设计成模仿人类行为，在特定的情绪范围内做出响应并遵循一套价值观。本文旨在利用LLMs根据大五人格模型模拟人格特质。研究表明，生成与人格相关的文本对模型而言仍是一项具有挑战性的任务。因此，我们提出了一个包含预定义大五人格特征的生成文本数据集，并提供了一个分析框架，用于测试LLMs的人格模拟能力。
英文摘要：
With the advancement of large language models (LLMs), the focus in Conversational AI has shifted from merely generating coherent and relevant responses to tackling more complex challenges, such as personalizing dialogue systems. In an effort to enhance user engagement, chatbots are often designed to mimic human behaviour, responding within a defined emotional spectrum and aligning to a set of values. In this paper, we aim to simulate personal traits according to the Big Five model with the use of LLMs. Our research showed that generating personality-related texts is still a challenging task for the models. As a result, we present a dataset of generated texts with the predefined Big Five characteristics and provide an analytical framework for testing LLMs on a simulation of personality skills.
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。
