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pro vyhledávání: '"Preum, Sarah M."'
Prior works formulate the extraction of event-specific arguments as a span extraction problem, where event arguments are explicit -- i.e. assumed to be contiguous spans of text in a document. In this study, we revisit this definition of Event Extract
Externí odkaz:
http://arxiv.org/abs/2410.03594
Autor:
Basak, Madhusudan, Sharif, Omar, Lord, Sarah E., Borodovsky, Jacob T., Marsch, Lisa A., Springer, Sandra A., Nunes, Edward, Brackett, Charlie D., ArchiBald, Luke J., Preum, Sarah M.
Background: One of the key FDA-approved medications for Opioid Use Disorder (OUD) is buprenorphine. Despite its popularity, individuals often report various information needs regarding buprenorphine treatment on social media platforms like Reddit. Ho
Externí odkaz:
http://arxiv.org/abs/2410.01633
Autor:
Nepal, Subigya, Pillai, Arvind, Campbell, William, Massachi, Talie, Heinz, Michael V., Kunwar, Ashmita, Choi, Eunsol Soul, Xu, Orson, Kuc, Joanna, Huckins, Jeremy, Holden, Jason, Preum, Sarah M., Depp, Colin, Jacobson, Nicholas, Czerwinski, Mary, Granholm, Eric, Campbell, Andrew T.
Mental health concerns are prevalent among college students, highlighting the need for effective interventions that promote self-awareness and holistic well-being. MindScape pioneers a novel approach to AI-powered journaling by integrating passively
Externí odkaz:
http://arxiv.org/abs/2409.09570
Internet memes have become a powerful means for individuals to express emotions, thoughts, and perspectives on social media. While often considered as a source of humor and entertainment, memes can also disseminate hateful content targeting individua
Externí odkaz:
http://arxiv.org/abs/2403.10829
In this paper, we develop an LLM-powered framework for the curation and evaluation of emerging opinion mining in online health communities. We formulate emerging opinion mining as a pairwise stance detection problem between (title, comment) pairs sou
Externí odkaz:
http://arxiv.org/abs/2403.03336
Large Language Models for Document-Level Event-Argument Data Augmentation for Challenging Role Types
Event Argument Extraction (EAE) is an extremely difficult information extraction problem -- with significant limitations in few-shot cross-domain (FSCD) settings. A common solution to FSCD modeling is data augmentation. Unfortunately, existing augmen
Externí odkaz:
http://arxiv.org/abs/2403.03304
Autor:
Yildirim, Nur, Zlotnikov, Susanna, Sayar, Deniz, Kahn, Jeremy M., Bukowski, Leigh A., Amin, Sher Shah, Riman, Kathryn A., Davis, Billie S., Minturn, John S., King, Andrew J., Ricketts, Dan, Tang, Lu, Sivaraman, Venkatesh, Perer, Adam, Preum, Sarah M., McCann, James, Zimmerman, John
Advances in artificial intelligence (AI) have enabled unprecedented capabilities, yet innovation teams struggle when envisioning AI concepts. Data science teams think of innovations users do not want, while domain experts think of innovations that ca
Externí odkaz:
http://arxiv.org/abs/2402.13437
Multimodal hateful content detection is a challenging task that requires complex reasoning across visual and textual modalities. Therefore, creating a meaningful multimodal representation that effectively captures the interplay between visual and tex
Externí odkaz:
http://arxiv.org/abs/2402.09738
Autor:
Gatto, Joseph, Preum, Sarah M.
User-generated texts available on the web and social platforms are often long and semantically challenging, making them difficult to annotate. Obtaining human annotation becomes increasingly difficult as problem domains become more specialized. For e
Externí odkaz:
http://arxiv.org/abs/2309.09877
Autor:
Sharif, Omar, Basak, Madhusudan, Parvin, Tanzia, Scharfstein, Ava, Bradham, Alphonso, Borodovsky, Jacob T., Lord, Sarah E., Preum, Sarah M.
Social media sites have become a popular platform for individuals to seek and share health information. Despite the progress in natural language processing for social media mining, a gap remains in analyzing health-related texts on social discourse i
Externí odkaz:
http://arxiv.org/abs/2308.09156