Zobrazeno 1 - 10
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pro vyhledávání: '"Sun Xiaojie"'
Autor:
Sun Xiaojie
Publikováno v:
SHS Web of Conferences, Vol 171, p 02026 (2023)
Due to the profound connotation of the great founding spirit of the Communist Party of China, integrating such great spirit into the ideological and political education in colleges and universities meets the needs of colleges and universities to carr
Externí odkaz:
https://doaj.org/article/fa2aeea6ec5c4025a03cb742f79e8412
Multi-aspect dense retrieval aims to incorporate aspect information (e.g., brand and category) into dual encoders to facilitate relevance matching. As an early and representative multi-aspect dense retriever, MADRAL learns several extra aspect embedd
Externí odkaz:
http://arxiv.org/abs/2401.03648
Autor:
Sun, Xiaojie, Bi, Keping, Guo, Jiafeng, Yang, Sihui, Zhang, Qishen, Liu, Zhongyi, Zhang, Guannan, Cheng, Xueqi
Dense retrieval methods have been mostly focused on unstructured text and less attention has been drawn to structured data with various aspects, e.g., products with aspects such as category and brand. Recent work has proposed two approaches to incorp
Externí odkaz:
http://arxiv.org/abs/2312.02538
Publikováno v:
E3S Web of Conferences, Vol 185, p 03022 (2020)
the purpose of this study was to explore the effect of “modular” nursing intervention on Ranoxifene in the treatment of patients with postmenopausal osteoporosis. A total of 108 patients with postmenopausal osteoporosis who were accepted by the D
Externí odkaz:
https://doaj.org/article/f1ff173545694bb1b4285049cfd59edc
Autor:
Sun, Xiaojie, Bi, Keping, Guo, Jiafeng, Ma, Xinyu, Yixing, Fan, Shan, Hongyu, Zhang, Qishen, Liu, Zhongyi
Grounded on pre-trained language models (PLMs), dense retrieval has been studied extensively on plain text. In contrast, there has been little research on retrieving data with multiple aspects using dense models. In the scenarios such as product sear
Externí odkaz:
http://arxiv.org/abs/2308.11474
An effective ranking model usually requires a large amount of training data to learn the relevance between documents and queries. User clicks are often used as training data since they can indicate relevance and are cheap to collect, but they contain
Externí odkaz:
http://arxiv.org/abs/2302.09340
Unbiased learning to rank (ULTR) aims to mitigate various biases existing in user clicks, such as position bias, trust bias, presentation bias, and learn an effective ranker. In this paper, we introduce our winning approach for the "Unbiased Learning
Externí odkaz:
http://arxiv.org/abs/2302.07530
Autor:
Sun, Xiaojie1,2 (AUTHOR) lanlan.chen@chnenergy.com.cn, Chen, Lanlan2 (AUTHOR), Feng, Wei1 (AUTHOR) xiaojie.sun@chnenergy.com.cn
Publikováno v:
Materials (1996-1944). Dec2024, Vol. 17 Issue 23, p6007. 10p.
Publikováno v:
In Water-Energy Nexus December 2024 7:187-199
Publikováno v:
In Journal of Environmental Chemical Engineering December 2024 12(6)