Zobrazeno 1 - 10
of 3 556
pro vyhledávání: '"Xiong,Yu"'
Autor:
Xiong, Yu, Chen, Yanping
This paper presents both a priori and a posteriori error analyses for a really pressure-robust virtual element method to approximate the incompressible Brinkman problem. We construct a divergence-preserving reconstruction operator using the Raviart-T
Externí odkaz:
http://arxiv.org/abs/2411.16067
Fine-tuning large language models (LLMs) with high parameter efficiency for downstream tasks has become a new paradigm. Low-Rank Adaptation (LoRA) significantly reduces the number of trainable parameters for fine-tuning. Although it has demonstrated
Externí odkaz:
http://arxiv.org/abs/2408.06854
Autor:
Ju, Xuan, Gao, Yiming, Zhang, Zhaoyang, Yuan, Ziyang, Wang, Xintao, Zeng, Ailing, Xiong, Yu, Xu, Qiang, Shan, Ying
Sora's high-motion intensity and long consistent videos have significantly impacted the field of video generation, attracting unprecedented attention. However, existing publicly available datasets are inadequate for generating Sora-like videos, as th
Externí odkaz:
http://arxiv.org/abs/2407.06358
Mamba, based on state space model (SSM) with its linear complexity and great success in classification provide its superiority in 3D point cloud analysis. Prior to that, Transformer has emerged as one of the most prominent and successful architecture
Externí odkaz:
http://arxiv.org/abs/2406.06069
Autor:
Li, Yin, Chen, Qi, Wang, Kai, Li, Meige, Si, Liping, Guo, Yingwei, Xiong, Yu, Wang, Qixing, Qin, Yang, Xu, Ling, van der Smagt, Patrick, Tang, Jun, Chen, Nutan
Multi-modality magnetic resonance imaging data with various sequences facilitate the early diagnosis, tumor segmentation, and disease staging in the management of nasopharyngeal carcinoma (NPC). The lack of publicly available, comprehensive datasets
Externí odkaz:
http://arxiv.org/abs/2404.03253
Autor:
Xiong, Yu, Hu, Zhipeng, Huang, Ye, Wu, Runze, Guan, Kai, Fang, Xingchen, Jiang, Ji, Zhou, Tianze, Hu, Yujing, Liu, Haoyu, Lyu, Tangjie, Fan, Changjie
Reinforcement Learning (RL) has demonstrated substantial potential across diverse fields, yet understanding its decision-making process, especially in real-world scenarios where rationality and safety are paramount, is an ongoing challenge. This pape
Externí odkaz:
http://arxiv.org/abs/2402.12685
Autor:
Li, Yin, Xiong, Yu, Fan, Wenxin, Wang, Kai, Yu, Qingqing, Si, Liping, van der Smagt, Patrick, Tang, Jun, Chen, Nutan
Objective: Subcutaneous Immunotherapy (SCIT) is the long-lasting causal treatment of allergic rhinitis (AR). How to enhance the adherence of patients to maximize the benefit of allergen immunotherapy (AIT) plays a crucial role in the management of AI
Externí odkaz:
http://arxiv.org/abs/2401.11447
Utilization of inter-base station cooperation for information processing has shown great potential in enhancing the overall quality of communication services (QoS) in wireless communication networks. Nevertheless, such cooperations require the knowle
Externí odkaz:
http://arxiv.org/abs/2401.11409
Self-supervised learning (SSL) for RGB images has achieved significant success, yet there is still limited research on SSL for infrared images, primarily due to three prominent challenges: 1) the lack of a suitable large-scale infrared pre-training d
Externí odkaz:
http://arxiv.org/abs/2312.08192
Autor:
Guo, Ze-Shi, Xing, Dan, Xi, Xiong-Yu, Liang, Cun-Guang, Hao, Bin, Zeng, Xiaojia, Tang, Hong, Chen, Huaican, Yin, Wen, Zhang, Peng, Zhou, Kefa, Zheng, Qingbin, Ma, Peng-Cheng
Many countries and commercial organizations have shown great interest in constructing Martian base. In-situ resource utilization (ISRU) provides a cost-effective way to achieve this ambitious goal. In this paper, we proposed to use Martian soil simul
Externí odkaz:
http://arxiv.org/abs/2401.06223