<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="berger-etal-2024-dreaming">
    <titleInfo>
        <title>Dreaming with ChatGPT: Unraveling the Challenges of LLMs Dream Generation</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Harel</namePart>
        <namePart type="family">Berger</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Hadar</namePart>
        <namePart type="family">King</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Omer</namePart>
        <namePart type="family">David</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 1st Workshop on NLP for Science (NLP4Science)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Lotem</namePart>
            <namePart type="family">Peled-Cohen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Nitay</namePart>
            <namePart type="family">Calderon</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Shir</namePart>
            <namePart type="family">Lissak</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Roi</namePart>
            <namePart type="family">Reichart</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Miami, FL, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Large Language Models (LLMs), such as ChatGPT, are used daily for different human-like text generation tasks. This motivates us to ask: 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.</abstract>
    <identifier type="citekey">berger-etal-2024-dreaming</identifier>
    <location>
        <url>https://aclanthology.org/2024.nlp4science-1.11</url>
    </location>
    <part>
        <date>2024-11</date>
        <extent unit="page">
            <start>140</start>
            <end>147</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Dreaming with ChatGPT: Unraveling the Challenges of LLMs Dream Generation
%A Berger, Harel
%A King, Hadar
%A David, Omer
%Y Peled-Cohen, Lotem
%Y Calderon, Nitay
%Y Lissak, Shir
%Y Reichart, Roi
%S Proceedings of the 1st Workshop on NLP for Science (NLP4Science)
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, FL, USA
%F berger-etal-2024-dreaming
%X Large Language Models (LLMs), such as ChatGPT, are used daily for different human-like text generation tasks. This motivates us to ask: 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.
%U https://aclanthology.org/2024.nlp4science-1.11
%P 140-147

Markdown (Informal)

[Dreaming with ChatGPT: Unraveling the Challenges of LLMs Dream Generation](https://aclanthology.org/2024.nlp4science-1.11) (Berger et al., NLP4Science 2024)

• Dreaming with ChatGPT: Unraveling the Challenges of LLMs Dream Generation (Berger et al., NLP4Science 2024)

ACL

• Harel Berger, Hadar King, and Omer David. 2024. Dreaming with ChatGPT: Unraveling the Challenges of LLMs Dream Generation. In Proceedings of the 1st Workshop on NLP for Science (NLP4Science), pages 140–147, Miami, FL, USA. Association for Computational Linguistics.