Zobrazeno 1 - 10
of 3 609
pro vyhledávání: '"Sekhon P"'
In the realm of Large Language Models (LLMs), prompt optimization is crucial for model performance. Although previous research has explored aspects like rephrasing prompt contexts, using various prompting techniques (like in-context learning and chai
Externí odkaz:
http://arxiv.org/abs/2411.10541
Autor:
You, Chenyu, Min, Yifei, Dai, Weicheng, Sekhon, Jasjeet S., Staib, Lawrence, Duncan, James S.
Fine-tuning pre-trained vision-language models, like CLIP, has yielded success on diverse downstream tasks. However, several pain points persist for this paradigm: (i) directly tuning entire pre-trained models becomes both time-intensive and computat
Externí odkaz:
http://arxiv.org/abs/2403.07241
Autor:
Chan, Colleen, You, Kisung, Chung, Sunny, Giuffrè, Mauro, Saarinen, Theo, Rajashekar, Niroop, Pu, Yuan, Shin, Yeo Eun, Laine, Loren, Wong, Ambrose, Kizilcec, René, Sekhon, Jasjeet, Shung, Dennis
Applications of large language models (LLMs) like ChatGPT have potential to enhance clinical decision support through conversational interfaces. However, challenges of human-algorithmic interaction and clinician trust are poorly understood. GutGPT, a
Externí odkaz:
http://arxiv.org/abs/2312.10072
Autor:
Saurabh Tripathi, Anureet Kaur, Ajmer Singh Brar, Karamjit Singh Sekhon, Sukhpreet Singh, Anurag Malik, Ozgur Kisi
Publikováno v:
BMC Plant Biology, Vol 24, Iss 1, Pp 1-17 (2024)
Abstract A multi-season research trial entitled ‘crop residue management effects on yield and water productivity of summer mung bean (Vigna radiata L.) under different irrigation regimes in Indian Punjab’ was conducted at Punjab Agricultural Univ
Externí odkaz:
https://doaj.org/article/2c334fa441134feba367b163aeb54a53
Deep learning research has uncovered the phenomenon of benign overfitting for overparameterized statistical models, which has drawn significant theoretical interest in recent years. Given its simplicity and practicality, the ordinary least squares (O
Externí odkaz:
http://arxiv.org/abs/2309.15769
Autor:
You, Chenyu, Dai, Weicheng, Min, Yifei, Staib, Lawrence, Sekhon, Jasjeet S., Duncan, James S.
Medical data often exhibits long-tail distributions with heavy class imbalance, which naturally leads to difficulty in classifying the minority classes (i.e., boundary regions or rare objects). Recent work has significantly improved semi-supervised m
Externí odkaz:
http://arxiv.org/abs/2304.02689
Publikováno v:
AAAI 2023
Recent NLP literature has seen growing interest in improving model interpretability. Along this direction, we propose a trainable neural network layer that learns a global interaction graph between words and then selects more informative words using
Externí odkaz:
http://arxiv.org/abs/2302.02016
Autor:
Zahinoor Ismail, Dylan X. Guan, Daniella Vellone, Clive Ballard, Byron Creese, Anne Corbett, Ellie Pickering, Adam Bloomfield, Adam Hampshire, Ramnik Sekhon, Pamela Roach, Eric E. Smith
Publikováno v:
Aging and Health Research, Vol 4, Iss 4, Pp 100207- (2024)
Background: : Preventing or reducing the risk of cognitive decline and dementia is of great public health interest. Longitudinal data from diverse samples are needed to properly inform clinicians, researchers, and policy makers. CAN-PROTECT is a rece
Externí odkaz:
https://doaj.org/article/34fe00bdf3dd44f88aa6c856806521c0
Autor:
Breanna K. Nelson, Lea N. Farah, Ava Grier, Wayne Su, Johnson Chen, Vesna Sossi, Mypinder S. Sekhon, A. Jon Stoessl, Cheryl Wellington, William G. Honer, Donna Lang, Noah D. Silverberg, William J. Panenka
Publikováno v:
NeuroImage, Vol 300, Iss , Pp 120859- (2024)
Background: The pathophysiology of protracted symptoms after COVID-19 is unclear. This study aimed to determine if long-COVID is associated with differences in baseline characteristics, markers of white matter diffusivity in the brain, and lower scor
Externí odkaz:
https://doaj.org/article/a4447bd59eac4f668b6311c649a267a5
Autor:
N. Kaushal, F. A. Lechleitner, M. Wilhelm, K. Azennoud, J. C. Bühler, K. Braun, Y. Ait Brahim, A. Baker, Y. Burstyn, L. Comas-Bru, J. Fohlmeister, Y. Goldsmith, S. P. Harrison, I. G. Hatvani, K. Rehfeld, M. Ritzau, V. Skiba, H. M. Stoll, J. G. Szűcs, P. Tanos, P. C. Treble, V. Azevedo, J. L. Baker, A. Borsato, S. Chawchai, A. Columbu, L. Endres, J. Hu, Z. Kern, A. Kimbrough, K. Koç, M. Markowska, B. Martrat, S. Masood Ahmad, C. Nehme, V. F. Novello, C. Pérez-Mejías, J. Ruan, N. Sekhon, N. Sinha, C. V. Tadros, B. H. Tiger, S. Warken, A. Wolf, H. Zhang
Publikováno v:
Earth System Science Data, Vol 16, Pp 1933-1963 (2024)
Palaeoclimate information on multiple climate variables at different spatiotemporal scales is becoming increasingly important to understand environmental and societal responses to climate change. A lack of high-quality reconstructions of past hydrocl
Externí odkaz:
https://doaj.org/article/7ae9dd200877447a8aa57fd9560d4ba7