Zobrazeno 1 - 10
of 1 854
pro vyhledávání: '"Wang Jinpeng"'
Publikováno v:
Zhongguo cuzhong zazhi, Vol 17, Iss 8, Pp 829-833 (2022)
目的 研究高海拔地区缺血性卒中患者单核细胞/HDL-C比值（monocyte/HDL-C ratio，MHR）与颅内动脉粥样硬化性狭窄（intracranial atherosclerotic stenosis，ICSA）程度的相关性。 方法 回顾性连续纳入2017年6
Externí odkaz:
https://doaj.org/article/18db7d1f3e8a4e8db82f09ec0335ccdc
Autor:
Wang, Jinpeng, Lian, Niu, Li, Jun, Wang, Yuting, Feng, Yan, Chen, Bin, Zhang, Yongbing, Xia, Shu-Tao
Self-supervised video hashing (SSVH) is a practical task in video indexing and retrieval. Although Transformers are predominant in SSVH for their impressive temporal modeling capabilities, they often suffer from computational and memory inefficiencie
Externí odkaz:
http://arxiv.org/abs/2412.14518
Adaptation of pretrained vision-language models such as CLIP to various downstream tasks have raised great interest in recent researches. Previous works have proposed a variety of test-time adaptation (TTA) methods to achieve strong generalization wi
Externí odkaz:
http://arxiv.org/abs/2410.15430
Autor:
Zhang, Taolin, Pan, Junwei, Wang, Jinpeng, Zha, Yaohua, Dai, Tao, Chen, Bin, Luo, Ruisheng, Deng, Xiaoxiang, Wang, Yuan, Yue, Ming, Jiang, Jie, Xia, Shu-Tao
With recent advances in large language models (LLMs), there has been emerging numbers of research in developing Semantic IDs based on LLMs to enhance the performance of recommendation systems. However, the dimension of these embeddings needs to match
Externí odkaz:
http://arxiv.org/abs/2410.09560
Cross-domain recommendation has attracted substantial interest in industrial apps such as Meituan, which serves multiple business domains via knowledge transfer and meets the diverse interests of users. However, existing methods typically follow an i
Externí odkaz:
http://arxiv.org/abs/2407.20121
Autor:
Qin, Shiyu, Wang, Jinpeng, Zhou, Yimin, Chen, Bin, Luo, Tianci, An, Baoyi, Dai, Tao, Xia, Shutao, Wang, Yaowei
Learned visual compression is an important and active task in multimedia. Existing approaches have explored various CNN- and Transformer-based designs to model content distribution and eliminate redundancy, where balancing efficacy (i.e., rate-distor
Externí odkaz:
http://arxiv.org/abs/2405.15413
Given a text query, partially relevant video retrieval (PRVR) aims to retrieve untrimmed videos containing relevant moments. Due to the lack of moment annotations, the uncertainty lying in clip modeling and text-clip correspondence leads to major cha
Externí odkaz:
http://arxiv.org/abs/2405.13824
Deep quantization methods have shown high efficiency on large-scale image retrieval. However, current models heavily rely on ground-truth information, hindering the application of quantization in label-hungry scenarios. A more realistic demand is to
Externí odkaz:
http://arxiv.org/abs/2404.04998
Predicting click-through rates (CTR) is a fundamental task for Web applications, where a key issue is to devise effective models for feature interactions. Current methodologies predominantly concentrate on modeling feature interactions within an indi
Externí odkaz:
http://arxiv.org/abs/2404.02249
Autor:
Xu, Lanling, Tian, Zhen, Li, Bingqian, Zhang, Junjie, Wang, Jinpeng, Cai, Mingchen, Zhao, Wayne Xin
With the rapid development of recommender systems, there is increasing side information that can be employed to improve the recommendation performance. Specially, we focus on the utilization of the associated \emph{textual data} of items (eg product
Externí odkaz:
http://arxiv.org/abs/2402.18166