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class="help"><a href="https://info.arxiv.org/help">Help</a> | <a href="https://arxiv.org/search/advanced">Advanced Search</a></p> </div> <div class="control"> <div class="select is-small"> <select name="searchtype" aria-label="Field to search"> <option value="all" selected="selected">All fields</option> <option value="title">Title</option> <option value="author">Author</option> <option value="abstract">Abstract</option> <option value="comments">Comments</option> <option value="journal_ref">Journal reference</option> <option value="acm_class">ACM classification</option> <option value="msc_class">MSC classification</option> <option value="report_num">Report number</option> <option value="paper_id">arXiv identifier</option> <option value="doi">DOI</option> <option value="orcid">ORCID</option> <option value="author_id">arXiv author ID</option> <option value="help">Help pages</option> <option value="full_text">Full text</option> </select> </div> </div> <input type="hidden" name="source" 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name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option value="msc_class">MSC classification</option><option value="report_num">Report number</option><option value="paper_id">arXiv identifier</option><option value="doi">DOI</option><option value="orcid">ORCID</option><option value="license">License (URI)</option><option value="author_id">arXiv author ID</option><option value="help">Help pages</option><option value="full_text">Full text</option></select> <input id="query" name="query" type="text" value="Xu, S Y"> <ul id="abstracts"><li><input checked id="abstracts-0" name="abstracts" type="radio" value="show"> <label for="abstracts-0">Show abstracts</label></li><li><input id="abstracts-1" name="abstracts" type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.16732">arXiv:2409.16732</a> <span> [<a href="https://arxiv.org/pdf/2409.16732">pdf</a>, <a href="https://arxiv.org/format/2409.16732">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> "It Explains What I am Currently Going Through Perfectly to a Tee": Understanding User Perceptions on LLM-Enhanced Narrative Interventions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Bhattacharjee%2C+A">Ananya Bhattacharjee</a>, <a href="/search/cs?searchtype=author&query=Xu%2C+S+Y">Sarah Yi Xu</a>, <a href="/search/cs?searchtype=author&query=Rao%2C+P">Pranav Rao</a>, <a href="/search/cs?searchtype=author&query=Zeng%2C+Y">Yuchen Zeng</a>, <a href="/search/cs?searchtype=author&query=Meyerhoff%2C+J">Jonah Meyerhoff</a>, <a href="/search/cs?searchtype=author&query=Ahmed%2C+S+I">Syed Ishtiaque Ahmed</a>, <a href="/search/cs?searchtype=author&query=Mohr%2C+D+C">David C Mohr</a>, <a href="/search/cs?searchtype=author&query=Liut%2C+M">Michael Liut</a>, <a href="/search/cs?searchtype=author&query=Mariakakis%2C+A">Alex Mariakakis</a>, <a href="/search/cs?searchtype=author&query=Kornfield%2C+R">Rachel Kornfield</a>, <a href="/search/cs?searchtype=author&query=Williams%2C+J+J">Joseph Jay Williams</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2409.16732v2-abstract-short" style="display: inline;"> Stories about overcoming personal struggles can effectively illustrate the application of psychological theories in real life, yet they may fail to resonate with individuals' experiences. In this work, we employ large language models (LLMs) to create tailored narratives that acknowledge and address unique challenging thoughts and situations faced by individuals. Our study, involving 346 young adul… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.16732v2-abstract-full').style.display = 'inline'; document.getElementById('2409.16732v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.16732v2-abstract-full" style="display: none;"> Stories about overcoming personal struggles can effectively illustrate the application of psychological theories in real life, yet they may fail to resonate with individuals' experiences. In this work, we employ large language models (LLMs) to create tailored narratives that acknowledge and address unique challenging thoughts and situations faced by individuals. Our study, involving 346 young adults across two settings, demonstrates that LLM-enhanced stories were perceived to be better than human-written ones in conveying key takeaways, promoting reflection, and reducing belief in negative thoughts. These stories were not only seen as more relatable but also similarly authentic to human-written ones, highlighting the potential of LLMs in helping young adults manage their struggles. The findings of this work provide crucial design considerations for future narrative-based digital mental health interventions, such as the need to maintain relatability without veering into implausibility and refining the wording and tone of AI-enhanced content. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.16732v2-abstract-full').style.display = 'none'; document.getElementById('2409.16732v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 25 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2312.13581">arXiv:2312.13581</a> <span> [<a href="https://arxiv.org/pdf/2312.13581">pdf</a>, <a href="https://arxiv.org/format/2312.13581">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> Understanding the Role of Large Language Models in Personalizing and Scaffolding Strategies to Combat Academic Procrastination </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Bhattacharjee%2C+A">Ananya Bhattacharjee</a>, <a href="/search/cs?searchtype=author&query=Zeng%2C+Y">Yuchen Zeng</a>, <a href="/search/cs?searchtype=author&query=Xu%2C+S+Y">Sarah Yi Xu</a>, <a href="/search/cs?searchtype=author&query=Kulzhabayeva%2C+D">Dana Kulzhabayeva</a>, <a href="/search/cs?searchtype=author&query=Ma%2C+M">Minyi Ma</a>, <a href="/search/cs?searchtype=author&query=Kornfield%2C+R">Rachel Kornfield</a>, <a href="/search/cs?searchtype=author&query=Ahmed%2C+S+I">Syed Ishtiaque Ahmed</a>, <a href="/search/cs?searchtype=author&query=Mariakakis%2C+A">Alex Mariakakis</a>, <a href="/search/cs?searchtype=author&query=Czerwinski%2C+M+P">Mary P Czerwinski</a>, <a href="/search/cs?searchtype=author&query=Kuzminykh%2C+A">Anastasia Kuzminykh</a>, <a href="/search/cs?searchtype=author&query=Liut%2C+M">Michael Liut</a>, <a href="/search/cs?searchtype=author&query=Williams%2C+J+J">Joseph Jay Williams</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2312.13581v1-abstract-short" style="display: inline;"> Traditional interventions for academic procrastination often fail to capture the nuanced, individual-specific factors that underlie them. Large language models (LLMs) hold immense potential for addressing this gap by permitting open-ended inputs, including the ability to customize interventions to individuals' unique needs. However, user expectations and potential limitations of LLMs in this conte… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.13581v1-abstract-full').style.display = 'inline'; document.getElementById('2312.13581v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2312.13581v1-abstract-full" style="display: none;"> Traditional interventions for academic procrastination often fail to capture the nuanced, individual-specific factors that underlie them. Large language models (LLMs) hold immense potential for addressing this gap by permitting open-ended inputs, including the ability to customize interventions to individuals' unique needs. However, user expectations and potential limitations of LLMs in this context remain underexplored. To address this, we conducted interviews and focus group discussions with 15 university students and 6 experts, during which a technology probe for generating personalized advice for managing procrastination was presented. Our results highlight the necessity for LLMs to provide structured, deadline-oriented steps and enhanced user support mechanisms. Additionally, our results surface the need for an adaptive approach to questioning based on factors like busyness. These findings offer crucial design implications for the development of LLM-based tools for managing procrastination while cautioning the use of LLMs for therapeutic guidance. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.13581v1-abstract-full').style.display = 'none'; document.getElementById('2312.13581v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2023. </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary">  <div class="column"> <div class="columns"> <div 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