Zobrazeno 1 - 10
of 175 854
pro vyhledávání: '"A, Te"'
Autor:
Fu, Yi-Fu, Tu, Yu-Chieh, Cheng, Tzu-Ling, Lin, Cheng-Yu, Yang, Yi-Ting, Liu, Heng-Yi, Liao, Keng-Te, Juan, Da-Cheng, Lin, Shou-De
In this paper, we explore the foundational mechanisms of memorization and generalization in Large Language Models (LLMs), inspired by the functional specialization observed in the human brain. Our investigation serves as a case study leveraging speci
Externí odkaz:
http://arxiv.org/abs/2412.18497
Autor:
Beard, Corey, Robertson, Paul, Lubin, Jack, Han, Te, Holcomb, Rae, Premnath, Pranav, Butler, R. Paul, Dalba, Paul A., Holden, Brad, Blake, Cullen H., Diddams, Scott A., Gupta, Arvind F., Halverson, Samuel, Krolikowski, Daniel M., Li, Dan, Lin, Andrea S. J., Logsdon, Sarah E., Lubar, Emily, Mahadevan, Suvrath, McElwain, Michael W., Ninan, Joe P., Paredes, Leonardo A., Roy, Arpita, Schwab, Christian, Stefansson, Gudmundur, Terrien, Ryan C., Wright, Jason T.
Stellar activity contamination of radial velocity (RV) data is one of the top challenges plaguing the field of extreme precision RV (EPRV) science. Previous work has shown that photometry can be very effective at removing such signals from RV data, e
Externí odkaz:
http://arxiv.org/abs/2412.11329
Autor:
Vrugt, Michael te
There is a growing interest in the development of artificial neural networks that are implemented in a physical system. A major challenge in this context is that these networks are difficult to train since training here would require a change of phys
Externí odkaz:
http://arxiv.org/abs/2412.13212
Autor:
Zhang, Xiaoci, Zhang, Te, Zhuang, Zhaotong, Leng, Zixuan, Wei, Zixuan, Liu, Xinyang, Xiang, Junsen, Zhang, Shuai, Sun, Peijie
A comprehensive study of the low-temperature properties of YbNi$_4$Mg has revealed evidence of a superheavy-fermion state, characterized by a large electronic specific-heat coefficient $\gamma_0$ $\approx$ 5.65 J mol$^{-1}$ K$^{-2}$ and an elevated W
Externí odkaz:
http://arxiv.org/abs/2412.08043
Autor:
Zhang, Jie, Sun, Min-Te
Recent advancements in Spectral Graph Convolutional Networks (SpecGCNs) have led to state-of-the-art performance in various graph representation learning tasks. To exploit the potential of SpecGCNs, we analyze corresponding graph filters via polynomi
Externí odkaz:
http://arxiv.org/abs/2412.01789
Autor:
Yang, Te, Jia, Jian, Zhu, Xiangyu, Zhao, Weisong, Wang, Bo, Cheng, Yanhua, Li, Yan, Liu, Shengyuan, Chen, Quan, Jiang, Peng, Gai, Kun, Lei, Zhen
Large Language Models (LLMs) have strong instruction-following capability to interpret and execute tasks as directed by human commands. Multimodal Large Language Models (MLLMs) have inferior instruction-following ability compared to LLMs. However, th
Externí odkaz:
http://arxiv.org/abs/2411.15453
Autor:
Song, Yuhang, Gianni, Mario, Yang, Chenguang, Lin, Kunyang, Chiu, Te-Chuan, Nguyen, Anh, Lee, Chun-Yi
This paper addresses the challenge of fine-grained alignment in Vision-and-Language Navigation (VLN) tasks, where robots navigate realistic 3D environments based on natural language instructions. Current approaches use contrastive learning to align l
Externí odkaz:
http://arxiv.org/abs/2411.14811
Autor:
Ma, Chen-Te, Zhang, Hui
Our review of the lattice chiral fermion delves into some critical areas of lattice field theory. By abandoning Hermiticity, the non-Hermitian formulation circumvents the Nielsen-Ninomiya theorem while maintaining chiral symmetry, a novel approach. C
Externí odkaz:
http://arxiv.org/abs/2411.09886
We have drawn connections between the Sachdev-Ye-Kitaev model and the multi-orbit Hatsugei-Kohmoto model, emphasizing their similarities and differences regarding chaotic behaviors. The features of the spectral form factor, such as the dip-ramp-plate
Externí odkaz:
http://arxiv.org/abs/2411.08496
API Phonons is a Python software package to predict the transport dynamics of heat-carrying phonons. Using the powerful syntax of Python, this package provides modules and functions interfacing between different packages for atomistic simulations, la
Externí odkaz:
http://arxiv.org/abs/2411.07774