Zobrazeno 1 - 10
of 1 055
pro vyhledávání: '"Zhang,Zehua"'
Autor:
Xu, Rengan, Yang, Junjie, Xu, Yifan, Li, Hong, Liu, Xing, Shankar, Devashish, Zhang, Haoci, Liu, Meng, Li, Boyang, Hu, Yuxi, Tang, Mingwei, Zhang, Zehua, Zhang, Tunhou, Li, Dai, Chen, Sijia, Musumeci, Gian-Paolo, Zhai, Jiaqi, Zhu, Bill, Yan, Hong, Reddy, Srihari
The integration of hardware accelerators has significantly advanced the capabilities of modern recommendation systems, enabling the exploration of complex ranking paradigms previously deemed impractical. However, the GPU-based computational costs pre
Externí odkaz:
http://arxiv.org/abs/2409.15373
In frame-based vision, object detection faces substantial performance degradation under challenging conditions due to the limited sensing capability of conventional cameras. Event cameras output sparse and asynchronous events, providing a potential s
Externí odkaz:
http://arxiv.org/abs/2407.12582
Autor:
Tang, Mingwei, Liu, Meng, Li, Hong, Yang, Junjie, Wei, Chenglin, Li, Boyang, Li, Dai, Xu, Rengan, Xu, Yifan, Zhang, Zehua, Wang, Xiangyu, Liu, Linfeng, Xie, Yuelei, Liu, Chengye, Fawaz, Labib, Li, Li, Wang, Hongnan, Zhu, Bill, Reddy, Sri
In recommendation systems, high-quality user embeddings can capture subtle preferences, enable precise similarity calculations, and adapt to changing preferences over time to maintain relevance. The effectiveness of recommendation systems depends on
Externí odkaz:
http://arxiv.org/abs/2406.05898
We proposed an end-to-end system design towards utilizing Retrieval Augmented Generation (RAG) to improve the factual accuracy of Large Language Models (LLMs) for domain-specific and time-sensitive queries related to private knowledge-bases. Our syst
Externí odkaz:
http://arxiv.org/abs/2403.10446
We propose a mask pretraining method for Graph Neural Networks (GNNs) to improve their performance on fitting potential energy surfaces, particularly in water systems. GNNs are pretrained by recovering spatial information related to masked-out atoms
Externí odkaz:
http://arxiv.org/abs/2402.15921
Autor:
Zhang, Zehua1 (AUTHOR), Wang, Yuxiong1 (AUTHOR), Gao, Baoshan1 (AUTHOR), Liu, Bin1 (AUTHOR), Yu, Jinyu1 (AUTHOR), Zhou, Honglan1 (AUTHOR) hlzhou@jlu.edu.cn
Publikováno v:
Scientific Reports. 9/18/2024, Vol. 14 Issue 1, p1-8. 8p.
Link prediction tasks focus on predicting possible future connections. Most existing researches measure the likelihood of links by different similarity scores on node pairs and predict links between nodes. However, the similarity-based approaches hav
Externí odkaz:
http://arxiv.org/abs/2210.13795
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 3, Pp 755-767 (2024)
The increasingly large scale of location-based social networks (LBSN) promotes the rapid development of point-of-interest (POI) recommendation business. POI geospatial distance directly adopted by traditional methods is difficult to simulate the high
Externí odkaz:
https://doaj.org/article/834a236111804c588f18f8a71e5465ff
In recent years, deep learning-based approaches have significantly improved the performance of single-channel speech enhancement. However, due to the limitation of training data and computational complexity, real-time enhancement of full-band (48 kHz
Externí odkaz:
http://arxiv.org/abs/2203.07684
Autor:
Ye, Peng, Yang, Yusheng, Qu, Ying, Yang, Wenxin, Tan, Jiulin, Zhang, Chengmin, Sun, Dong, Zhang, Jie, Zhao, Weikang, Guo, Shuquan, Song, Lei, Hou, Tianyong, Zhang, Zehua, Tang, Yong, Limjunyawong, Nathachit, Xu, Jianzhong, Dong, Shiwu, Dou, Ce, Luo, Fei
Publikováno v:
In International Journal of Biological Macromolecules October 2024 277 Part 1