Zobrazeno 1 - 10
of 65 173
pro vyhledávání: '"Yangyang An"'
Autor:
Tun Wang, Sheng Liao, Peng Lu, Zhenyu He, Siyuan Cheng, Tianjian Wang, Zibo Cheng, Yangyang An, Mo Wang, Chang Shu
Publikováno v:
Materials Today Bio, Vol 30, Iss , Pp 101402- (2025)
Decellularized tissue-engineered vascular grafts (dTEVGs) exhibit superior biocompatibility, anti-infection properties and repair potential, contributing to better patency and making them a more ideal choice for arteriovenous grafts (AVGs) in hemodia
Externí odkaz:
https://doaj.org/article/d051f236605c4df4a7c92d8f91aa5415
Given a collection $\mathcal{D} =\{D_1,D_2,\ldots,D_m\}$ of digraphs on the common vertex set $V$, an $m$-edge digraph $H$ with vertices in $V$ is transversal in $\mathcal{D}$ if there exists a bijection $\varphi :E(H)\rightarrow [m]$ such that $e \i
Externí odkaz:
http://arxiv.org/abs/2501.00998
Autor:
Liu, Haotian, Wei, Zhiqing, Wang, Xiyang, Niu, Yangyang, Zhang, Yixin, Wu, Huici, Feng, Zhiyong
Integrated sensing and communication (ISAC) has emerged as a pivotal enabling technology for sixth-generation (6G) mobile communication system. The ISAC research in dense urban areas has been plaguing by severe multipath interference, propelling the
Externí odkaz:
http://arxiv.org/abs/2501.00297
Autor:
Li, Haohang, Cao, Yupeng, Yu, Yangyang, Javaji, Shashidhar Reddy, Deng, Zhiyang, He, Yueru, Jiang, Yuechen, Zhu, Zining, Subbalakshmi, Koduvayur, Xiong, Guojun, Huang, Jimin, Qian, Lingfei, Peng, Xueqing, Xie, Qianqian, Suchow, Jordan W.
Recent advancements have underscored the potential of large language model (LLM)-based agents in financial decision-making. Despite this progress, the field currently encounters two main challenges: (1) the lack of a comprehensive LLM agent framework
Externí odkaz:
http://arxiv.org/abs/2412.18174
With current state-of-the-art approaches aimed at enhancing the reasoning capabilities of Large Language Models(LLMs) through iterative preference learning inspired by AlphaZero, we propose to further enhance the step-wise reasoning capabilities thro
Externí odkaz:
http://arxiv.org/abs/2412.17397
Autor:
Li, Xinzhe, Zhan, Jiahui, He, Shengfeng, Xu, Yangyang, Dong, Junyu, Zhang, Huaidong, Du, Yong
Personalized image generation has made significant strides in adapting content to novel concepts. However, a persistent challenge remains: balancing the accurate reconstruction of unseen concepts with the need for editability according to the prompt,
Externí odkaz:
http://arxiv.org/abs/2412.15674
This technical report introduces our top-ranked solution that employs two approaches, \ie suffix injection and projected gradient descent (PGD) , to address the TiFA workshop MLLM attack challenge. Specifically, we first append the text from an incor
Externí odkaz:
http://arxiv.org/abs/2412.15614
Autor:
Tung, Chi-Huan, Ding, Lijie, Chang, Ming-Ching, Huang, Guan-Rong, Porcar, Lionel, Wang, Yangyang, Carrillo, Jan-Michael Y., Sumpter, Bobby G., Shinohara, Yuya, Do, Changwoo, Chen, Wei-Ren
Small-angle scattering (SAS) techniques are indispensable tools for probing the structure of soft materials. However, traditional analytical models often face limitations in structural inversion for complex systems, primarily due to the absence of cl
Externí odkaz:
http://arxiv.org/abs/2412.15474
We present a novel class of projected gradient (PG) methods for minimizing a smooth but not necessarily convex function over a convex compact set. We first provide a novel analysis of the "vanilla" PG method, achieving the best-known iteration comple
Externí odkaz:
http://arxiv.org/abs/2412.14291
This paper derives the stochastic homogenization for two dimensional Navier--Stokes equations with random coefficients. By means of weak convergence method and Stratonovich--Khasminskii averaging principle approach, the solution of two dimensional Na
Externí odkaz:
http://arxiv.org/abs/2412.12866