Zobrazeno 1 - 10
of 12 303
pro vyhledávání: '"P. Veloso"'
Publikováno v:
European Psychiatry, Vol 67, Pp S409-S410 (2024)
Introduction Cannabis is the most used recreational drug worldwide. Cannabinoids have long been known for their anti-emetic properties. Paradoxically, chronic cannabis consumption has been linked to inducing refractory nausea and vomiting, a conditio
Externí odkaz:
https://doaj.org/article/d113e3edc8e6417194e0261cd431a991
Publikováno v:
European Psychiatry, Vol 67, Pp S276-S276 (2024)
Introduction Philosophy of mind grapples with fundamental questions concerning the Consciousness, the Mind-body problem, the Identity, and Free will (as opposed to Determinism). In the context of psychiatry, this philosophical groundwork provides a c
Externí odkaz:
https://doaj.org/article/908489303ebb4160ab4df4795a629b21
Publikováno v:
European Psychiatry, Vol 66, Pp S1014-S1014 (2023)
Introduction Clozapine is the only available treatment for refractory schizophrenia and is rarely associated with the development of myocarditis. Usually, the onset of symptoms occurs within the first month of treatment. The symptoms of myocarditis i
Externí odkaz:
https://doaj.org/article/9e87ee7fbd3840f686d62b96fc3fd719
Publikováno v:
European Psychiatry, Vol 66, Pp S994-S995 (2023)
Introduction Susac Syndrome (SS) is an immune-mediated endotheliopathy that mainly affects young women. It is characterized by the typical triad: subacute encephalopathy, retinal vaso-occlusive disease, and hearing loss. Encephalopathy symptoms are v
Externí odkaz:
https://doaj.org/article/d0eae6ca79cd4f6aa8c5628f2dbf5ed8
Reward models (RMs) are a crucial component in the alignment of large language models' (LLMs) outputs with human values. RMs approximate human preferences over possible LLM responses to the same prompt by predicting and comparing reward scores. Howev
Externí odkaz:
http://arxiv.org/abs/2411.16502
Autor:
Verma, Gaurav, Kaur, Rachneet, Srishankar, Nishan, Zeng, Zhen, Balch, Tucker, Veloso, Manuela
State-of-the-art multimodal web agents, powered by Multimodal Large Language Models (MLLMs), can autonomously execute many web tasks by processing user instructions and interacting with graphical user interfaces (GUIs). Current strategies for buildin
Externí odkaz:
http://arxiv.org/abs/2411.13451
Autor:
Kawawa-Beaudan, Maxime, Sood, Srijan, Palande, Soham, Mani, Ganapathy, Balch, Tucker, Veloso, Manuela
Publikováno v:
NeurIPS 2024, Workshop on Behavioral Machine Learning
We investigate the use of sequence analysis for behavior modeling, emphasizing that sequential context often outweighs the value of aggregate features in understanding human behavior. We discuss framing common problems in fields like healthcare, fina
Externí odkaz:
http://arxiv.org/abs/2411.02174
Autor:
Thomas, Nancy, Rahimi, Saba, Vapsi, Annita, Ansell, Cathy, Christie, Elizabeth, Borrajo, Daniel, Balch, Tucker, Veloso, Manuela
Publikováno v:
IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (2024) 7746-7751
Amidst escalating climate change, hurricanes are inflicting severe socioeconomic impacts, marked by heightened economic losses and increased displacement. Previous research utilized nighttime light data to predict the impact of hurricanes on economic
Externí odkaz:
http://arxiv.org/abs/2410.22150
In this paper, we study the ability of large language models to learn specific mathematical rules such as distributivity or simplifying equations. We present an empirical analysis of their ability to generalize these rules, as well as to reuse them i
Externí odkaz:
http://arxiv.org/abs/2410.16973
Autor:
Zmigrod, Ran, Shetty, Pranav, Sibue, Mathieu, Ma, Zhiqiang, Nourbakhsh, Armineh, Liu, Xiaomo, Veloso, Manuela
The rise of large language models (LLMs) for visually rich document understanding (VRDU) has kindled a need for prompt-response, document-based datasets. As annotating new datasets from scratch is labor-intensive, the existing literature has generate
Externí odkaz:
http://arxiv.org/abs/2410.15484