Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Adithya, V."'
Autor:
Vu, Huy, Nguyen, Huy Anh, Ganesan, Adithya V, Juhng, Swanie, Kjell, Oscar N. E., Sedoc, Joao, Kern, Margaret L., Boyd, Ryan L., Ungar, Lyle, Schwartz, H. Andrew, Eichstaedt, Johannes C.
Artificial intelligence-based language generators are now a part of most people's lives. However, by default, they tend to generate "average" language without reflecting the ways in which people differ. Here, we propose a lightweight modification to
Externí odkaz:
http://arxiv.org/abs/2412.16882
Autor:
Ganesan, Adithya V, Varadarajan, Vasudha, Lal, Yash Kumar, Eijsbroek, Veerle C., Kjell, Katarina, Kjell, Oscar N. E., Dhanasekaran, Tanuja, Stade, Elizabeth C., Eichstaedt, Johannes C., Boyd, Ryan L., Schwartz, H. Andrew, Flek, Lucie
Use of large language models such as ChatGPT (GPT-4) for mental health support has grown rapidly, emerging as a promising route to assess and help people with mood disorders, like depression. However, we have a limited understanding of GPT-4's schema
Externí odkaz:
http://arxiv.org/abs/2411.13800
Autor:
Dey, Gourab, Ganesan, Adithya V, Lal, Yash Kumar, Shah, Manal, Sinha, Shreyashee, Matero, Matthew, Giorgi, Salvatore, Kulkarni, Vivek, Schwartz, H. Andrew
Social science NLP tasks, such as emotion or humor detection, are required to capture the semantics along with the implicit pragmatics from text, often with limited amounts of training data. Instruction tuning has been shown to improve the many capab
Externí odkaz:
http://arxiv.org/abs/2402.01980
Very large language models (LLMs) perform extremely well on a spectrum of NLP tasks in a zero-shot setting. However, little is known about their performance on human-level NLP problems which rely on understanding psychological concepts, such as asses
Externí odkaz:
http://arxiv.org/abs/2306.01183
Autor:
Mangalik, Siddharth, Eichstaedt, Johannes C., Giorgi, Salvatore, Mun, Jihu, Ahmed, Farhan, Gill, Gilvir, Ganesan, Adithya V., Subrahmanya, Shashanka, Soni, Nikita, Clouston, Sean A. P., Schwartz, H. Andrew
Compared to physical health, population mental health measurement in the U.S. is very coarse-grained. Currently, in the largest population surveys, such as those carried out by the Centers for Disease Control or Gallup, mental health is only broadly
Externí odkaz:
http://arxiv.org/abs/2302.12952
Autor:
Siddharth Mangalik, Johannes C. Eichstaedt, Salvatore Giorgi, Jihu Mun, Farhan Ahmed, Gilvir Gill, Adithya V. Ganesan, Shashanka Subrahmanya, Nikita Soni, Sean A. P. Clouston, H. Andrew Schwartz
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-12 (2024)
Abstract In the most comprehensive population surveys, mental health is only broadly captured through questionnaires asking about “mentally unhealthy days” or feelings of “sadness.” Further, population mental health estimates are predominantl
Externí odkaz:
https://doaj.org/article/3330a9b035644e88808b983c382a42af
In human-level NLP tasks, such as predicting mental health, personality, or demographics, the number of observations is often smaller than the standard 768+ hidden state sizes of each layer within modern transformer-based language models, limiting th
Externí odkaz:
http://arxiv.org/abs/2105.03484
Autor:
August Håkan Nilsson, Hansen Andrew Schwartz, Richard N. Rosenthal, James R. McKay, Huy Vu, Young-Min Cho, Syeda Mahwish, Adithya V. Ganesan, Lyle Ungar
Publikováno v:
PLoS ONE, Vol 19, Iss 3 (2024)
Externí odkaz:
https://doaj.org/article/0003ff840e6b471686a35da4b53d654a
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