Zobrazeno 1 - 10
of 295 629
pro vyhledávání: '"Hang, To"'
Large Language Models (LLMs) are increasingly used in everyday life and research. One of the most common use cases is conversational interactions, enabled by the language generation capabilities of LLMs. Just as between two humans, a conversation bet
Externí odkaz:
http://arxiv.org/abs/2410.17632
Autor:
Zhang, Xiao-Min, Zhao, Run-Qing, Peng, Zhi-peng, Li, Xi-Bin, Chu, Peng-Cheng, Feng, Yun-Cai, Xing, Yi-Hang
This study extended noncanonical warm inflation to the nonminimal derivative coupling scenario. The fundamental equations, including the evolution equations and the slow roll equations of this new framework, were derived. The enlarged damping term, w
Externí odkaz:
http://arxiv.org/abs/2410.16839
Autor:
Cheng, Zesen, Zhang, Hang, Li, Kehan, Leng, Sicong, Hu, Zhiqiang, Wu, Fei, Zhao, Deli, Li, Xin, Bing, Lidong
Contrastive loss is a powerful approach for representation learning, where larger batch sizes enhance performance by providing more negative samples to better distinguish between similar and dissimilar data. However, scaling batch sizes is constraine
Externí odkaz:
http://arxiv.org/abs/2410.17243
Autor:
Hang, Yanfeng
In this study, we investigate the canonical differential equations governing the two-site one-loop wavefcuntion coefficient in conformally-coupled scalar theory within a general FRW cosmology. By utilizing relative twisted cohomology and integration
Externí odkaz:
http://arxiv.org/abs/2410.17192
Autor:
Kwan, Chung-Hang, Leung, Wing Hong
In this article, we provide a "beyond-endoscopic" treatment of the functional equations for standard $L$-functions, building on ideas and techniques from Venkatesh's thesis and "spectral reciprocity".
Externí odkaz:
http://arxiv.org/abs/2410.16921
Real-world object manipulation has been commonly challenged by physical uncertainties and perception limitations. Being an effective strategy, while caging configuration-based manipulation frameworks have successfully provided robust solutions, they
Externí odkaz:
http://arxiv.org/abs/2410.16481
Autor:
Sun, Qiao, Wang, Huimin, Zhan, Jiahao, Nie, Fan, Wen, Xin, Xu, Leimeng, Zhan, Kun, Jia, Peng, Lang, Xianpeng, Zhao, Hang
Large real-world driving datasets have sparked significant research into various aspects of data-driven motion planners for autonomous driving. These include data augmentation, model architecture, reward design, training strategies, and planner pipel
Externí odkaz:
http://arxiv.org/abs/2410.15774
Autor:
Hallin, Marc, Liu, Hang
Increased attention has been given recently to the statistical analysis of variables with values on nonlinear manifolds. A natural but nontrivial problem in that context is the definition of quantile concepts. We are proposing a solution for compact
Externí odkaz:
http://arxiv.org/abs/2410.15711
Adaptation of pretrained vision-language models such as CLIP to various downstream tasks have raised great interest in recent researches. Previous works have proposed a variety of test-time adaptation (TTA) methods to achieve strong generalization wi
Externí odkaz:
http://arxiv.org/abs/2410.15430
In this paper, we employ the framework of localization algebras to compute the equivariant K-homology class of the Euler characteristic operator, a central object in studying equivariant index theory on manifolds. This approach provides a powerful al
Externí odkaz:
http://arxiv.org/abs/2410.15103