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pro vyhledávání: '"Wu, Shaohua"'
More and more research works fuse the LiDAR and camera information to improve the 3D object detection of the autonomous driving system. Recently, a simple yet effective fusion framework has achieved an excellent detection performance, fusing the LiDA
Externí odkaz:
http://arxiv.org/abs/2411.05292
Many fields could benefit from the rapid development of the large language models (LLMs). The end-to-end autonomous driving (e2eAD) is one of the typically fields facing new opportunities as the LLMs have supported more and more modalities. Here, by
Externí odkaz:
http://arxiv.org/abs/2407.21293
Performance evaluation of particular channel coding has been a significant topic in coding theory, often involving the use of bounding techniques. This paper focuses on the new family of capacity-achieving codes, Spinal codes, to provide a comprehens
Externí odkaz:
http://arxiv.org/abs/2407.03741
Autor:
Wu, Shaohua, Luo, Jiangang, Chen, Xi, Li, Lingjun, Zhao, Xudong, Yu, Tong, Wang, Chao, Wang, Yue, Wang, Fei, Qiao, Weixu, He, Houbo, Zhang, Zeru, Sun, Zeyu, Mao, Junxiong, Shen, Chong
Yuan 2.0-M32, with a similar base architecture as Yuan-2.0 2B, uses a mixture-of-experts architecture with 32 experts of which 2 experts are active. A new router network, Attention Router, is proposed and adopted for a more efficient selection of exp
Externí odkaz:
http://arxiv.org/abs/2405.17976
In this paper, we study a remote monitoring system where a receiver observes a remote binary Markov source and decides whether to sample and transmit the state through a randomly delayed channel. We adopt uncertainty of information (UoI), defined as
Externí odkaz:
http://arxiv.org/abs/2405.02924
Age of Information (AoI) has been recognized as an important metric to measure the freshness of information. Central to this consensus is that minimizing AoI can enhance the freshness of information, thereby facilitating the accuracy of subsequent de
Externí odkaz:
http://arxiv.org/abs/2405.02042
Split learning (SL) is a promising approach for training artificial intelligence (AI) models, in which devices collaborate with a server to train an AI model in a distributed manner, based on a same fixed split point. However, due to the device heter
Externí odkaz:
http://arxiv.org/abs/2403.05158
In the coming sixth generation (6G) communication era, to provide seamless and ubiquitous connections, the space-air-ground-sea integrated network (SAGSIN) is envisioned to address the challenges of communication coverage in areas with difficult cond
Externí odkaz:
http://arxiv.org/abs/2402.14297
Autor:
Wu, Shaohua, Zhao, Xudong, Wang, Shenling, Luo, Jiangang, Li, Lingjun, Chen, Xi, Zhao, Bing, Wang, Wei, Yu, Tong, Zhang, Rongguo, Zhang, Jiahua, Wang, Chao
In this work, we develop and release Yuan 2.0, a series of large language models with parameters ranging from 2.1 billion to 102.6 billion. The Localized Filtering-based Attention (LFA) is introduced to incorporate prior knowledge of local dependenci
Externí odkaz:
http://arxiv.org/abs/2311.15786
In this letter, we introduce an efficient method for estimating weight distributions of polar codes and polarization-adjusted convolutional (PAC) codes. Based on a recursive algorithm of computing the weight enumerating functions of polar cosets, thi
Externí odkaz:
http://arxiv.org/abs/2310.08226