Zobrazeno 1 - 10
of 1 398
pro vyhledávání: '"Zhang, Ruoyu"'
Autor:
Fang, Ruijie, Zhang, Ruoyu, Hosseini, Elahe, Fang, Chongzhou, Eslaminehr, Mahdi, Rafatirad, Setareh, Homayoun, Houman
Automated emotion recognition has applications in various fields, such as human-machine interaction, healthcare, security, education, and emotion-aware recommendation/feedback systems. Developing methods to analyze human emotions accurately is essent
Externí odkaz:
http://arxiv.org/abs/2409.06118
Advanced Energy-Efficient System for Precision Electrodermal Activity Monitoring in Stress Detection
This paper presents a novel Electrodermal Activity (EDA) signal acquisition system, designed to address the challenges of stress monitoring in contemporary society, where stress affects one in four individuals. Our system focuses on enhancing the acc
Externí odkaz:
http://arxiv.org/abs/2409.06114
In this letter, we investigate the channel estimation problem for MIMO wireless communication systems with movable antennas (MAs) at both the transmitter (Tx) and receiver (Rx). To achieve high channel estimation accuracy with low pilot training over
Externí odkaz:
http://arxiv.org/abs/2407.18773
Simulated Patients (SPs) play a crucial role in clinical medical education by providing realistic scenarios for student practice. However, the high cost of training and hiring qualified SPs, along with the heavy workload and potential risks they face
Externí odkaz:
http://arxiv.org/abs/2404.13066
Due to photon-assisted transport processes, chiral edge modes induced by periodic driving do not directly mediate quantized transport. Here we show how narrow bandwidth "energy filters" can restore quantization by suppressing photon assisted transpor
Externí odkaz:
http://arxiv.org/abs/2402.18776
Autor:
Zeng, Shulin, Liu, Jun, Dai, Guohao, Yang, Xinhao, Fu, Tianyu, Wang, Hongyi, Ma, Wenheng, Sun, Hanbo, Li, Shiyao, Huang, Zixiao, Dai, Yadong, Li, Jintao, Wang, Zehao, Zhang, Ruoyu, Wen, Kairui, Ning, Xuefei, Wang, Yu
Transformer-based Large Language Models (LLMs) have made a significant impact on various domains. However, LLMs' efficiency suffers from both heavy computation and memory overheads. Compression techniques like sparsification and quantization are comm
Externí odkaz:
http://arxiv.org/abs/2401.03868
Publikováno v:
IEEE Transactions on Wireless Communications, 2024
Benefitting from the vast spatial degrees of freedom, the amalgamation of integrated sensing and communication (ISAC) and massive multiple-input multiple-output (MIMO) is expected to simultaneously improve spectral and energy efficiencies as well as
Externí odkaz:
http://arxiv.org/abs/2401.01738
Prevalent supervised learning methods in natural language processing (NLP) are notoriously data-hungry, which demand large amounts of high-quality annotated data. In practice, acquiring such data is a costly endeavor. Recently, the superior few-shot
Externí odkaz:
http://arxiv.org/abs/2310.19596
Autor:
Fang, Chongzhou, Miao, Ning, Srivastav, Shaurya, Liu, Jialin, Zhang, Ruoyu, Fang, Ruijie, Asmita, Tsang, Ryan, Nazari, Najmeh, Wang, Han, Homayoun, Houman
Large language models (LLMs) have demonstrated significant potential in the realm of natural language understanding and programming code processing tasks. Their capacity to comprehend and generate human-like code has spurred research into harnessing
Externí odkaz:
http://arxiv.org/abs/2310.12357
Large Language Models (LLMs) can acquire extensive world knowledge through pre-training on large corpora. However, due to exposure to low-quality data, LLMs may exhibit harmful behavior without aligning with human values. The dominant approach for st
Externí odkaz:
http://arxiv.org/abs/2310.00212