Divergent Creativity in Humans and Large Language Models
<|reference_start|>Divergent Creativity in Humans and Large Language Models: The recent surge in the capabilities of Large Language Models (LLMs) has led to claims that they are approaching a level of creativity akin to human capabilities. This idea has sparked a blend of excitement and apprehension. However, a critical piece that has been missing in this discourse is a systematic evaluation of LLM creativity, particularly in comparison to human divergent thinking. To bridge this gap, we leverage recent advances in creativity science to build a framework for in-depth analysis of divergent creativity in both state-of-the-art LLMs and a substantial dataset of 100,000 humans. We found evidence suggesting that LLMs can indeed surpass human capabilities in specific creative tasks such as divergent association and creative writing. Our quantitative benchmarking framework opens up new paths for the development of more creative LLMs, but it also encourages more granular inquiries into the distinctive elements that constitute human inventive thought processes, compared to those that can be artificially generated.<|reference_end|>
@article{bellemare-pepin2024divergent,
    title={Divergent Creativity in Humans and Large Language Models},
    author={Antoine Bellemare-Pepin (1 and 2), Franc{c}ois Lespinasse (3),
  Philipp Th"olke (1), Yann Harel (1), Kory Mathewson (4), Jay A. Olson (5),
  Yoshua Bengio (4 and 6) and Karim Jerbi (1, 4 and 7) ((1) CoCo Lab,
  Psychology department, Universit'e de Montr'eal, Montreal, QC, Canada, (2)
  Music department, Concordia University, Montreal, QC, Canada, (3) Sociology
  and Anthropology department, Concordia University, Montreal, QC, Canada, (4)
  Mila (Quebec AI research Institute), Montreal, QC, Canada, (5) Department of
  Psychology, University of Toronto Mississauga, Mississauga, ON, Canada, (6)
  Department of Computer Science and Operations Research, Universit'e de
  Montr'eal, Montreal, QC, Canada, (7) UNIQUE Center (Quebec Neuro-AI research
  Center), QC, Canada)},
    journal={arXiv preprint arXiv:2405.13012},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.13012},
    primaryClass={cs.CL cs.AI}
}