PersonaLLM
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[NAACL Findings 2024] PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits
PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits
This repo contains the official code for running LLM persona
experiments and subsequent analyses in the PersonaLLM paper.
Simulate LLM personas
We first create 10 personas for each of 32 personality types.
conda activate audiencenlp
python3.9 run_bfi.py --model "GPT-3.5-turbo-0613"
python3.9 run_bfi.py --model "GPT-4-0613"
python3.9 run_bfi.py --model "llama-2"
Generate stories with LLM personas
python3.9 run_creative_writing.py --model "GPT-3.5-turbo-0613"
python3.9 run_creative_writing.py --model "GPT-4-0613"
python3.9 run_creative_writing.py --model "llama-2"
References
If you use this repository in your research, please kindly cite our paper:
@article{jiang2023personallm,
title={PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits},
author={Hang Jiang and Xiajie Zhang and Xubo Cao and Cynthia Breazeal and Deb Roy and Jad Kabbara},
booktitle = "Findings of the Association for Computational Linguistics: NAACL 2024",
year={2024}
}
Acknowledgement
PersonaLLM is a research program from MIT Center for Constructive Communication (@mit-ccc), MIT Media Lab, and Stanford University. We are interested in drawing from social and cognitive sciences to understand the behaviors of foundation models.