Zobrazeno 1 - 10
of 1 202
pro vyhledávání: '"Chen Yuhan"'
Autor:
Bin Liu, Xinguang Yu, Qing Chang, Di Liu, Yanyang Zhang, Junpeng Xu, Haonan Yang, Zhiqi Mao, Guosong Shang, Shuzhen Liu, Zhebin Feng, Chen Yuhan
Publikováno v:
BMJ Open, Vol 14, Iss 10 (2024)
Introduction Deep brain stimulation (DBS) and vagus nerve stimulation (VNS) can improve motor function in patients with poststroke hemiplegia. No comparison study exists.Methods and analysis This is a randomised, double-blind, controlled clinical tri
Externí odkaz:
https://doaj.org/article/09bb160ea4d44a7ca05d5f8b4bdc6c49
Publikováno v:
Shipin Kexue, Vol 45, Iss 9, Pp 243-251 (2024)
Human milk is the most important source of nutrition in early infancy, which can meet all the nutritional needs in the first 6 months after birth. It contains many bioactive substances that can regulate the intestinal flora, promote the development o
Externí odkaz:
https://doaj.org/article/6c883342664b433db3f4e1bcdea5b980
Autor:
Ye, Haojie, Xia, Yuchen, Chen, Yuhan, Chen, Kuan-Yu, Yuan, Yichao, Deng, Shuwen, Kasikci, Baris, Mudge, Trevor, Talati, Nishil
Oblivious RAM (ORAM) hides the memory access patterns, enhancing data privacy by preventing attackers from discovering sensitive information based on the sequence of memory accesses. The performance of ORAM is often limited by its inherent trade-off
Externí odkaz:
http://arxiv.org/abs/2411.05400
Many positional encodings (PEs) are designed to exhibit long-term decay, based on an entrenched and long-standing inductive opinion: tokens farther away from the current position carry less relevant information. We argue that long-term decay is outda
Externí odkaz:
http://arxiv.org/abs/2410.21216
Autor:
Luo, Yihong, Chen, Yuhan, Qiu, Siya, Wang, Yiwei, Zhang, Chen, Zhou, Yan, Cao, Xiaochun, Tang, Jing
Graph Neural Networks (GNNs) have shown superior performance in node classification. However, GNNs perform poorly in the Few-Shot Node Classification (FSNC) task that requires robust generalization to make accurate predictions for unseen classes with
Externí odkaz:
http://arxiv.org/abs/2410.16845
Due to the cost-prohibitive nature of training Large Language Models (LLMs), fine-tuning has emerged as an attractive alternative for specializing LLMs for specific tasks using limited compute resources in a cost-effective manner. In this paper, we c
Externí odkaz:
http://arxiv.org/abs/2408.04693
Autor:
Dong, Peijie, Li, Lujun, Zhong, Yuedong, Du, Dayou, Fan, Ruibo, Chen, Yuhan, Tang, Zhenheng, Wang, Qiang, Xue, Wei, Guo, Yike, Chu, Xiaowen
In this paper, we present the first structural binarization method for LLM compression to less than 1-bit precision. Although LLMs have achieved remarkable performance, their memory-bound nature during the inference stage hinders the adoption of reso
Externí odkaz:
http://arxiv.org/abs/2408.01803
Autor:
Zhu, Yutao, Zhou, Kun, Mao, Kelong, Chen, Wentong, Sun, Yiding, Chen, Zhipeng, Cao, Qian, Wu, Yihan, Chen, Yushuo, Wang, Feng, Zhang, Lei, Li, Junyi, Wang, Xiaolei, Wang, Lei, Zhang, Beichen, Dong, Zican, Cheng, Xiaoxue, Chen, Yuhan, Tang, Xinyu, Hou, Yupeng, Ren, Qiangqiang, Pang, Xincheng, Xie, Shufang, Zhao, Wayne Xin, Dou, Zhicheng, Mao, Jiaxin, Lin, Yankai, Song, Ruihua, Xu, Jun, Chen, Xu, Yan, Rui, Wei, Zhewei, Hu, Di, Huang, Wenbing, Gao, Ze-Feng, Chen, Yueguo, Lu, Weizheng, Wen, Ji-Rong
Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many open-source LLMs have been released with technical reports, the lack of
Externí odkaz:
http://arxiv.org/abs/2406.19853
Many studies have revealed that large language models (LLMs) exhibit uneven awareness of different contextual positions. Their limited context awareness can lead to overlooking critical information and subsequent task failures. While several approach
Externí odkaz:
http://arxiv.org/abs/2406.19598
We prove the low Mach number limit from compressible Navier-Stokes-Fourier system with the general pressure law around a constant state on the torus $\mathbb{T}^N_a$. We view this limit as a special case of the weakly nonlinear-dissipative approximat
Externí odkaz:
http://arxiv.org/abs/2406.12642