Papers by Rezvaneh Rezapour
Tales of Morality: Comparing Human- and LLM-Generated Moral Stories from Visual Cues (2025.findings-emnlp)
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| Challenge: | a recent study has found that stories are central to how humans communicate moral values . |
| Approach: | They compare human- and LLM-generated moral narratives based on images annotated by humans for moral content . authors propose a framework for evaluating moral storytelling in vision-language models . |
| Outcome: | The proposed model compared human- and LLM-generated narratives on images . human stories reflect a balanced distribution of moral foundations and coherent narrative arcs, but LLMs emphasize Care foundation and lack emotional resolution. |
Words Matter: Reducing Stigma in Online Conversations about Substance Use with Large Language Models (2024.emnlp-main)
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| Challenge: | Only 7% of people living with an SUD receive any form of treatment, with stigma reported as a major barrier. |
| Approach: | They propose a computational framework for analyzing stigma and de-stigmatizing online content and delving into the linguistic features that propagate stigma towards PWUS. |
| Outcome: | The proposed model transforms stigmatizing language into more empathetic language and analyzes over 1.2 million posts on social media . |
From Conversation to Automation: Leveraging LLMs for Problem-Solving Therapy Analysis (2025.findings-acl)
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| Challenge: | Problem-Solving Therapy (PST) is a structured psychological approach that helps individuals manage stress and resolve personal issues. |
| Approach: | They developed a framework for PST annotation using established PST Core Strategies and a set of novel Facilitative Strategies to analyze a corpus of real-world therapy transcripts to determine which strategies are most prevalent. |
| Outcome: | The proposed framework outperforms existing models and LLMs to identify the most prevalent strategies in a corpus of real-world therapy transcripts. |
Detecting Extraneous Content in Podcasts (2021.eacl-main)
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| Challenge: | Podcast episodes often contain extraneous material interleaved within the audio and the written descriptions . authors present classifiers that leverage both textual and listening patterns to detect such content . |
| Approach: | They propose a classifier that leverages both textual and listening patterns to detect extraneous material in podcast descriptions and audio transcripts. |
| Outcome: | The proposed classifiers improve ROUGE scores and reduce extraneous content in podcast summarization tasks. |
An Empirical Methodology for Detecting and Prioritizing Needs during Crisis Events (2020.findings-emnlp)
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| Challenge: | Social media platforms such as Twitter contain a vast amount of information about the general public’s needs. |
| Approach: | They propose to use Twitter to extract a list of needed resources and detecting sentences that specify who-needs-what resources. |
| Outcome: | The proposed methods achieve 0.64 precision on a set of 1,000 annotated tweets and achieve 0.68 F1-score. |
Detecting Impact Relevant Sections in Scientific Research (2024.lrec-main)
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| Challenge: | Impact assessment is an evolving area of research that aims at measuring and predicting the potential effects of projects or programs. |
| Approach: | They propose a framework for automatically assessing the impact of scientific research by identifying pertinent sections in project reports that indicate potential impacts. |
| Outcome: | The proposed method achieves accuracy scores up to 0.81 and is generalizable to scientific research from different domains and languages. |
100,000 Podcasts: A Spoken English Document Corpus (2020.coling-main)
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Ann Clifton, Sravana Reddy, Yongze Yu, Aasish Pappu, Rezvaneh Rezapour, Hamed Bonab, Maria Eskevich, Gareth Jones, Jussi Karlgren, Ben Carterette, Rosie Jones
| Challenge: | Podcasts are a large and growing repository of spoken audio. |
| Approach: | They propose to use podcasts as a resource for speech processing and linguistics . they use a corpus of 100,000 podcasts to study the complexity of the domain . |
| Outcome: | The Spotify Podcast Dataset is the largest corpus of transcribed speech data . the dataset contains 60,000 hours of podcasts, with a range of genres and styles . |
Like a Therapist, But Not: Reddit Narratives of AI in Mental Health Contexts (2026.findings-acl)
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| Challenge: | Large language models are increasingly used for emotional support and mental health–related interactions outside clinical settings. |
| Approach: | They analyze 5,126 Reddit posts describing use of AI for emotional support or therapy . positive sentiment is most strongly associated with task and goal alignment, they say . |
| Outcome: | The proposed framework analyzes language, adoption-related attitudes, and relational alignment at scale. positive sentiment is most strongly associated with task and goal alignment. |
Beyond Citations: Corpus-based Methods for Detecting the Impact of Research Outcomes on Society (2020.lrec-1)
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| Challenge: | Existing methods for assessing the impact of research are ineffective for identifying impact beyond academia and text-based indicators beyond those that capture attention. |
| Approach: | They propose a deductive and inductive approach to categorize research impact categories using a corpus-based approach . they use a combination of deductive methods and machine learning to infer impact categories from project reports. |
| Outcome: | The proposed method predicts deductively and inductively derived impact categories with 76.39% accuracy and 78.81% accuracy. |