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:

@inproceedings{jiang-etal-2024-personallm,
    title = "{P}ersona{LLM}: Investigating the Ability of Large Language Models to Express Personality Traits",
    author = "Jiang, Hang  and
      Zhang, Xiajie  and
      Cao, Xubo  and
      Breazeal, Cynthia  and
      Roy, Deb  and
      Kabbara, Jad",
    editor = "Duh, Kevin  and
      Gomez, Helena  and
      Bethard, Steven",
    booktitle = "Findings of the Association for Computational Linguistics: NAACL 2024",
    month = jun,
    year = "2024",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.findings-naacl.229",
    pages = "3605--3627",
}

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.