@inproceedings{berger-etal-2024-dreaming,
    title = "Dreaming with {C}hat{GPT}: Unraveling the Challenges of {LLM}s Dream Generation",
    author = "Berger, Harel  and
      King, Hadar  and
      David, Omer",
    editor = "Peled-Cohen, Lotem  and
      Calderon, Nitay  and
      Lissak, Shir  and
      Reichart, Roi",
    booktitle = "Proceedings of the 1st Workshop on NLP for Science (NLP4Science)",
    month = nov,
    year = "2024",
    address = "Miami, FL, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2024.nlp4science-1.11/",
    doi = "10.18653/v1/2024.nlp4science-1.11",
    pages = "140--147",
    abstract = "Large Language Models (LLMs), such as ChatGPT, are used daily for different human-like text generation tasks. This motivates us to ask: \textit{Can an LLM generate human dreams?} For this research, we explore this new avenue through the lens of ChatGPT, and its ability to generate valid dreams. We have three main findings: (i) Chatgpt-4o, the new version of chatGPT, generated all requested dreams. (ii) Generated dreams meet key psychological criteria of dreams. We hope our work will set the stage for developing a new task of dream generation for LLMs. This task can help psychologists evaluate patients' dreams based on their demographic factors."
}