Zobrazeno 1 - 10
of 263
pro vyhledávání: '"LU Wenhao"'
Quantization has been substantially adopted to accelerate inference and reduce memory consumption of large language models (LLMs). While activation-weight joint quantization speeds up the inference process through low-precision kernels, we demonstrat
Externí odkaz:
http://arxiv.org/abs/2410.11305
Publikováno v:
Di-san junyi daxue xuebao, Vol 43, Iss 4, Pp 283-294 (2021)
Objective To investigate the roles of electroacupuncture (EA) in the upregulation of zinc finger protein Cezanne and in its neuroprotective effect on inflammatory injury induced by focal cerebral ischemia/reperfusion (I/R) in rats. Methods SD rats we
Externí odkaz:
https://doaj.org/article/dab177f5fdbd468ba1faf3a0b5d4b6fc
Can emergent language models faithfully model the intelligence of decision-making agents? Though modern language models exhibit already some reasoning ability, and theoretically can potentially express any probable distribution over tokens, it remain
Externí odkaz:
http://arxiv.org/abs/2406.18505
The state of an object reflects its current status or condition and is important for a robot's task planning and manipulation. However, detecting an object's state and generating a state-sensitive plan for robots is challenging. Recently, pre-trained
Externí odkaz:
http://arxiv.org/abs/2406.09988
As a sequel to our previous work [C. Ma, Q. Zhang and W. Zheng, SIAM J. Numer. Anal., 60 (2022)], [C. Ma and W. Zheng, J. Comput. Phys. 469 (2022)], this paper presents a generic framework of arbitrary Lagrangian-Eulerian unfitted finite element (ALE
Externí odkaz:
http://arxiv.org/abs/2404.15624
Although there has been rapid progress in endowing robots with the ability to solve complex manipulation tasks, generating control policies for bimanual robots to solve tasks involving two hands is still challenging because of the difficulties in eff
Externí odkaz:
http://arxiv.org/abs/2404.02018
Autor:
Lu, Wenhao, Zhao, Xufeng, Fryen, Thilo, Lee, Jae Hee, Li, Mengdi, Magg, Sven, Wermter, Stefan
Reinforcement learning (RL) is a powerful technique for training intelligent agents, but understanding why these agents make specific decisions can be quite challenging. This lack of transparency in RL models has been a long-standing problem, making
Externí odkaz:
http://arxiv.org/abs/2401.00104
Autor:
Zhao, Xufeng, Li, Mengdi, Lu, Wenhao, Weber, Cornelius, Lee, Jae Hee, Chu, Kun, Wermter, Stefan
Recent advancements in large language models have showcased their remarkable generalizability across various domains. However, their reasoning abilities still have significant room for improvement, especially when confronted with scenarios requiring
Externí odkaz:
http://arxiv.org/abs/2309.13339
Autor:
Zhang, Zhengyuan, Jin, Haoran, Zheng, Zesheng, Zhang, Wenwen, Lu, Wenhao, Qin, Feng, Sharma, Arunima, Pramanik, Manojit, Zheng, Yuanjin
Photoacoustic microscopy (PAM) is a novel implementation of photoacoustic imaging (PAI) for visualizing the 3D bio-structure, which is realized by raster scanning of the tissue. However, as three involved critical imaging parameters, imaging speed, l
Externí odkaz:
http://arxiv.org/abs/2308.04922
In this paper, we study a priori error estimates for the finite element approximation of the nonlinear Schr\"{o}dinger-Poisson model. The electron density is defined by an infinite series over all eigenvalues of the Hamiltonian operator. To establish
Externí odkaz:
http://arxiv.org/abs/2307.09703