Year: 2023
Type: conference-paper
Abstract: Large language models (LLMs) can be used to serve as agents to simulate human behaviors, given the powerful ability to understand human instructions and provide high-quality generated texts.Such ability stimulates us to wonder whether LLMs can simulate a person in a higher form than simple human behaviors.Therefore, we aim to train an agent with the profile, experience, and emotional states of a specific person instead of using limited prompts to instruct ChatGPT API.In this work, we introduce Character-LLM that teach LLMs to act as specific people such as Beethoven, Queen Cleopatra, Julius Caesar, etc.Our method focuses on editing profiles as experiences of a certain character and training models to be personal simulacra with these experiences.To assess the effectiveness of our approach, we build a test playground that interviews trained agents and evaluates whether the agents memorize their characters and experiences.Experimental results show interesting observations that help build future simulacra of humankind.1
Authors: Yunfan Shao, Linyang Li, Junqi Dai, Xipeng Qiu
Institutions: Fudan University, Shanghai Artificial Intelligence Laboratory
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Awards: G1817111062, G460263832
OpenAlex ID: W4389519488