Zobrazeno 1 - 10
of 393
pro vyhledávání: '"Chen Yilong"'
Autor:
Chen Yilong
Publikováno v:
Contemporary Social Sciences (2024)
With the reform of the New National College Entrance Examination(Gaokao), the nongraded education will become an inevitable trend. In senior high school, the traditional test-oriented education is popular. The knowledge is mainly taught by the teache
Externí odkaz:
https://doaj.org/article/8849cfd56b584d5787d66656f9559e67
Autor:
Tang, Chuanyu, Chen, Yilong, Zhang, Zhenyu, Shang, Junyuan, Zhang, Wenyuan, Huang, Yong, Liu, Tingwen
Low-Rank Adaptation (LoRA) drives research to align its performance with full fine-tuning. However, significant challenges remain: (1) Simply increasing the rank size of LoRA does not effectively capture high-rank information, which leads to a perfor
Externí odkaz:
http://arxiv.org/abs/2410.13408
This letter exploits moving arrays to enable nearfield multiple-input multiple-output (MIMO) sensing via a limited number of antenna elements. We consider a scenario where a base station (BS) is equipped with a uniform linear array (ULA) on a moving
Externí odkaz:
http://arxiv.org/abs/2410.09358
Emojis have gained immense popularity on social platforms, serving as a common means to supplement or replace text. However, existing data mining approaches generally either completely ignore or simply treat emojis as ordinary Unicode characters, whi
Externí odkaz:
http://arxiv.org/abs/2409.14552
Autor:
Chen, Yilong, Xu, Zongyi, Huang, Xiaoshui, Zhao, Shanshan, Jiang, Xinqi, Gao, Xinyu, Gao, Xinbo
Compared to single-modal knowledge distillation, cross-modal knowledge distillation faces more severe challenges due to domain gaps between modalities. Although various methods have proposed various solutions to overcome these challenges, there is st
Externí odkaz:
http://arxiv.org/abs/2409.02438
This paper considers a multi-functional orthogonal frequency division multiplexing (OFDM) system with integrated sensing, communication, and powering (ISCAP), in which a multi-antenna base station (BS) transmits OFDM signals to simultaneously deliver
Externí odkaz:
http://arxiv.org/abs/2408.14156
Autor:
Chen, Yilong, Wang, Guoxia, Shang, Junyuan, Cui, Shiyao, Zhang, Zhenyu, Liu, Tingwen, Wang, Shuohuan, Sun, Yu, Yu, Dianhai, Wu, Hua
Large Language Models (LLMs) have ignited an innovative surge of AI applications, marking a new era of exciting possibilities equipped with extended context windows. However, hosting these models is cost-prohibitive mainly due to the extensive memory
Externí odkaz:
http://arxiv.org/abs/2408.03675
Autor:
Chen, Yilong, Zhang, Linhao, Shang, Junyuan, Zhang, Zhenyu, Liu, Tingwen, Wang, Shuohuan, Sun, Yu
Large language models (LLMs) with billions of parameters demonstrate impressive performance. However, the widely used Multi-Head Attention (MHA) in LLMs incurs substantial computational and memory costs during inference. While some efforts have optim
Externí odkaz:
http://arxiv.org/abs/2406.06567
Weakly supervised LiDAR semantic segmentation has made significant strides with limited labeled data. However, most existing methods focus on the network training under weak supervision, while efficient annotation strategies remain largely unexplored
Externí odkaz:
http://arxiv.org/abs/2404.12861
Deep learning models have become a powerful tool in knee angle estimation for lower limb prostheses, owing to their adaptability across various gait phases and locomotion modes. Current methods utilize Multi-Layer Perceptrons (MLP), Long-Short Term M
Externí odkaz:
http://arxiv.org/abs/2404.06772