Zobrazeno 1 - 10
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pro vyhledávání: '"Schwartz, H. P."'
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
Hard x-ray imaging is indispensable across diverse fields owing to its high penetrability. However, the resolution of traditional x-ray imaging modalities, such as computed tomography (CT) systems, is constrained by factors including beam properties,
Externí odkaz:
http://arxiv.org/abs/2402.14023
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
Pre-trained language models consider the context of neighboring words and documents but lack any author context of the human generating the text. However, language depends on the author's states, traits, social, situational, and environmental attribu
Externí odkaz:
http://arxiv.org/abs/2401.12492
Mental health issues differ widely among individuals, with varied signs and symptoms. Recently, language-based assessments have shown promise in capturing this diversity, but they require a substantial sample of words per person for accuracy. This wo
Externí odkaz:
http://arxiv.org/abs/2311.06467
As research in human-centered NLP advances, there is a growing recognition of the importance of incorporating human and social factors into NLP models. At the same time, our NLP systems have become heavily reliant on LLMs, most of which do not model
Externí odkaz:
http://arxiv.org/abs/2312.07751
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:
Giorgi, Salvatore, Havaldar, Shreya, Ahmed, Farhan, Akhtar, Zuhaib, Vaidya, Shalaka, Pan, Gary, Ungar, Lyle H., Schwartz, H. Andrew, Sedoc, Joao
We present metrics for evaluating dialog systems through a psychologically-grounded "human" lens in which conversational agents express a diversity of both states (e.g., emotion) and traits (e.g., personality), just as people do. We present five inte
Externí odkaz:
http://arxiv.org/abs/2305.14757
X-ray imaging is a prevalent technique for non-invasively visualizing the interior of the human body and opaque instruments. In most commercial x-ray modalities, an image is formed by measuring the x-rays that pass through the object of interest. How
Externí odkaz:
http://arxiv.org/abs/2305.12468
Autor:
Varadarajan, Vasudha, Juhng, Swanie, Mahwish, Syeda, Liu, Xiaoran, Luby, Jonah, Luhmann, Christian, Schwartz, H. Andrew
While transformer-based systems have enabled greater accuracies with fewer training examples, data acquisition obstacles still persist for rare-class tasks -- when the class label is very infrequent (e.g. < 5% of samples). Active learning has in gene
Externí odkaz:
http://arxiv.org/abs/2305.02459