Zobrazeno 1 - 10
of 113 280
pro vyhledávání: '"A Goh"'
Autor:
Dodo, T., Cheoun, M. K., Choi, J. H., Choi, J. Y., Goh, J., Haga, K., Harada, M., Hasegawa, S., Hwang, W., Jang, H. I., Jang, J. S., Joo, K. K., Jung, D. E., Kang, S. K., Kasugai, Y., Kawasaki, T., Kim, E. M., Kim, S. Y., Kim, S. B., Kinoshita, H., Konno, T., Lee, D. H., Little, C., Maruyama, T., Marzec, E., Masuda, S., Meigo, S., Moon, D. H., Nakano, T., Niiyama, M., Nishikawa, K., Pac, M. Y., Park, B. J., Park, H. W., Park, J. B., Park, J. S., Park, R. G., Peeters, S. J. M., Ryu, J. W., Sakai, K., Sakamoto, S., Shima, T., Shin, C. D., Spitz, J., Suekane, F., Sugaya, Y., Suzuya, K., Yamaguchi, Y., Yeo, I. S., Yu, I.
JSNS$^2$ (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment searching for sterile neutrinos through the observation of $\bar{\nu}_{\mu} \rightarrow \bar{\nu}_e$ appearance oscillations, using neutrinos produced by m
Externí odkaz:
http://arxiv.org/abs/2412.18509
AI-generated content (AIGC), such as advertisement copy, product descriptions, and social media posts, is becoming ubiquitous in business practices. However, the value of AI-generated metadata, such as titles, remains unclear on user-generated conten
Externí odkaz:
http://arxiv.org/abs/2412.18337
Dealing with missing data poses significant challenges in predictive analysis, often leading to biased conclusions when oversimplified assumptions about the missing data process are made. In cases where the data are missing not at random (MNAR), join
Externí odkaz:
http://arxiv.org/abs/2412.14946
Autor:
Brodeur, Peter G., Buckley, Thomas A., Kanjee, Zahir, Goh, Ethan, Ling, Evelyn Bin, Jain, Priyank, Cabral, Stephanie, Abdulnour, Raja-Elie, Haimovich, Adrian, Freed, Jason A., Olson, Andrew, Morgan, Daniel J., Hom, Jason, Gallo, Robert, Horvitz, Eric, Chen, Jonathan, Manrai, Arjun K., Rodman, Adam
Performance of large language models (LLMs) on medical tasks has traditionally been evaluated using multiple choice question benchmarks. However, such benchmarks are highly constrained, saturated with repeated impressive performance by LLMs, and have
Externí odkaz:
http://arxiv.org/abs/2412.10849
Autor:
Feng, Chun-Mei, He, Yuanyang, Zou, Jian, Khan, Salman, Xiong, Huan, Li, Zhen, Zuo, Wangmeng, Goh, Rick Siow Mong, Liu, Yong
Publikováno v:
International Journal of Computer Vision, 2025
Existing test-time prompt tuning (TPT) methods focus on single-modality data, primarily enhancing images and using confidence ratings to filter out inaccurate images. However, while image generation models can produce visually diverse images, single-
Externí odkaz:
http://arxiv.org/abs/2412.09706
Autor:
Huang, Zitong, Chen, Ze, Li, Yuanze, Dong, Bowen, Zhou, Erjin, Liu, Yong, Goh, Rick Siow Mong, Feng, Chun-Mei, Zuo, Wangmeng
Few-Shot Class-Incremental Learning has shown remarkable efficacy in efficient learning new concepts with limited annotations. Nevertheless, the heuristic few-shot annotations may not always cover the most informative samples, which largely restricts
Externí odkaz:
http://arxiv.org/abs/2412.06642
Autor:
Cremonesi, Francesco, Innocenti, Lucia, Ourselin, Sebastien, Goh, Vicky, Antonelli, Michela, Lorenzi, Marco
Background. Federated learning (FL) has gained wide popularity as a collaborative learning paradigm enabling collaborative AI in sensitive healthcare applications. Nevertheless, the practical implementation of FL presents technical and organizational
Externí odkaz:
http://arxiv.org/abs/2412.06494
The symmetric teleparallel theory offers an alternative gravitational formulation which can elucidate events in the early and late universe without requiring the physical existence of dark matter or dark energy. In this formalism, $f(Q, C)$ gravity h
Externí odkaz:
http://arxiv.org/abs/2412.05382
The classical shadows protocol, introduced by Huang et al. [Nat. Phys. 16, 1050 (2020)], makes use of the median-of-means (MoM) estimator to efficiently estimate the expectation values of $M$ observables with failure probability $\delta$ using only $
Externí odkaz:
http://arxiv.org/abs/2412.03381
We characterize gap-opening mechanisms in the topological heavy fermion (THF) model of magic-angle twisted bilayer graphene (MATBG), with and without electron-phonon coupling, using dynamical mean-field theory (DMFT) with the numerical renormalizatio
Externí odkaz:
http://arxiv.org/abs/2412.03108