Zobrazeno 1 - 10
of 13 845
pro vyhledávání: '"A. Subhashini"'
Seeking answers to questions within long scientific research articles is a crucial area of study that aids readers in quickly addressing their inquiries. However, existing question-answering (QA) datasets based on scientific papers are limited in sca
Externí odkaz:
http://arxiv.org/abs/2407.09413
Autor:
Subhashini Kaligotla
Publikováno v:
caa.reviews.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf012acc9d6429c84c6385281f87b655
https://doi.org/10.3202/caa.reviews.2022.38
https://doi.org/10.3202/caa.reviews.2022.38
Autor:
Lee, Mina, Gero, Katy Ilonka, Chung, John Joon Young, Shum, Simon Buckingham, Raheja, Vipul, Shen, Hua, Venugopalan, Subhashini, Wambsganss, Thiemo, Zhou, David, Alghamdi, Emad A., August, Tal, Bhat, Avinash, Choksi, Madiha Zahrah, Dutta, Senjuti, Guo, Jin L. C., Hoque, Md Naimul, Kim, Yewon, Knight, Simon, Neshaei, Seyed Parsa, Sergeyuk, Agnia, Shibani, Antonette, Shrivastava, Disha, Shroff, Lila, Stark, Jessi, Sterman, Sarah, Wang, Sitong, Bosselut, Antoine, Buschek, Daniel, Chang, Joseph Chee, Chen, Sherol, Kreminski, Max, Park, Joonsuk, Pea, Roy, Rho, Eugenia H., Shen, Shannon Zejiang, Siangliulue, Pao
In our era of rapid technological advancement, the research landscape for writing assistants has become increasingly fragmented across various research communities. We seek to address this challenge by proposing a design space as a structured way to
Externí odkaz:
http://arxiv.org/abs/2403.14117
Autor:
Pan, Haining, Mudur, Nayantara, Taranto, Will, Tikhanovskaya, Maria, Venugopalan, Subhashini, Bahri, Yasaman, Brenner, Michael P., Kim, Eun-Ah
Large language models (LLMs) have demonstrated an unprecedented ability to perform complex tasks in multiple domains, including mathematical and scientific reasoning. We demonstrate that with carefully designed prompts, LLMs can accurately carry out
Externí odkaz:
http://arxiv.org/abs/2403.03154
Autor:
Kanchan, Namrata B.1 namrata.kanchan@utexas.edu
Publikováno v:
Material Religion. Jul-Sep2024, Vol. 20 Issue 3/4, p315-317. 3p.
Conference
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Abbreviation expansion is a strategy used to speed up communication by limiting the amount of typing and using a language model to suggest expansions. Here we look at personalizing a Large Language Model's (LLM) suggestions based on prior conversatio
Externí odkaz:
http://arxiv.org/abs/2312.14327
Autor:
Cai, Shanqing, Venugopalan, Subhashini, Seaver, Katie, Xiao, Xiang, Tomanek, Katrin, Jalasutram, Sri, Morris, Meredith Ringel, Kane, Shaun, Narayanan, Ajit, MacDonald, Robert L., Kornman, Emily, Vance, Daniel, Casey, Blair, Gleason, Steve M., Nelson, Philip Q., Brenner, Michael P.
Finding ways to accelerate text input for individuals with profound motor impairments has been a long-standing area of research. Closing the speed gap for augmentative and alternative communication (AAC) devices such as eye-tracking keyboards is impo
Externí odkaz:
http://arxiv.org/abs/2312.01532
Autor:
Yang, Samuel J., Li, Shutong, Venugopalan, Subhashini, Tshitoyan, Vahe, Aykol, Muratahan, Merchant, Amil, Cubuk, Ekin Dogus, Cheon, Gowoon
Machine learning is transforming materials discovery by providing rapid predictions of material properties, which enables large-scale screening for target materials. However, such models require training data. While automated data extraction from sci
Externí odkaz:
http://arxiv.org/abs/2311.13778
Autor:
Shanqing Cai, Subhashini Venugopalan, Katie Seaver, Xiang Xiao, Katrin Tomanek, Sri Jalasutram, Meredith Ringel Morris, Shaun Kane, Ajit Narayanan, Robert L. MacDonald, Emily Kornman, Daniel Vance, Blair Casey, Steve M. Gleason, Philip Q. Nelson, Michael P. Brenner
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-18 (2024)
Abstract Accelerating text input in augmentative and alternative communication (AAC) is a long-standing area of research with bearings on the quality of life in individuals with profound motor impairments. Recent advances in large language models (LL
Externí odkaz:
https://doaj.org/article/028c427245d94b0b92a7319f9750017f