28 min listen
Character-LLM: A Trainable Agent for Role-Playing
Character-LLM: A Trainable Agent for Role-Playing
ratings:
Length:
33 minutes
Released:
Oct 23, 2023
Format:
Podcast episode
Description
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 \textit{memorize} their characters and experiences. Experimental results show interesting observations that help build future simulacra of humankind.
2023: Yunfan Shao, Linyang Li, Junqi Dai, Xipeng Qiu
https://arxiv.org/pdf/2310.10158v1.pdf
2023: Yunfan Shao, Linyang Li, Junqi Dai, Xipeng Qiu
https://arxiv.org/pdf/2310.10158v1.pdf
Released:
Oct 23, 2023
Format:
Podcast episode
Titles in the series (100)
LISA: Reasoning Segmentation via Large Language Model: Although perception systems have made remarkable advancements in recent years, they still rely on explicit human instruction to identify the target objects or categories before executing visual recognition tasks. Such systems lack the ability to acti... by Papers Read on AI