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pro vyhledávání: '"Tan, Shicheng"'
Long-Context Question Answering (LCQA), a challenging task, aims to reason over long-context documents to yield accurate answers to questions. Existing long-context Large Language Models (LLMs) for LCQA often struggle with the "lost in the middle" is
Externí odkaz:
http://arxiv.org/abs/2410.18050
Hyperbolic Neural Networks (HNNs), operating in hyperbolic space, have been widely applied in recent years, motivated by the existence of an optimal embedding in hyperbolic space that can preserve data hierarchical relationships (termed Hierarchical
Externí odkaz:
http://arxiv.org/abs/2402.02478
Autor:
Tan, Shicheng, Tam, Weng Lam, Wang, Yuanchun, Gong, Wenwen, Yang, Yang, Tang, Hongyin, He, Keqing, Liu, Jiahao, Wang, Jingang, Zhao, Shu, Zhang, Peng, Tang, Jie
Currently, the reduction in the parameter scale of large-scale pre-trained language models (PLMs) through knowledge distillation has greatly facilitated their widespread deployment on various devices. However, the deployment of knowledge distillation
Externí odkaz:
http://arxiv.org/abs/2306.06629
Autor:
Tan, Shicheng, Tam, Weng Lam, Wang, Yuanchun, Gong, Wenwen, Zhao, Shu, Zhang, Peng, Tang, Jie
The large scale of pre-trained language models poses a challenge for their deployment on various devices, with a growing emphasis on methods to compress these models, particularly knowledge distillation. However, current knowledge distillation method
Externí odkaz:
http://arxiv.org/abs/2306.06625
Distributed document representation is one of the basic problems in natural language processing. Currently distributed document representation methods mainly consider the context information of words or sentences. These methods do not take into accou
Externí odkaz:
http://arxiv.org/abs/2201.02846
Publikováno v:
In Neurocomputing 13 November 2019 366:97-108
Akademický článek
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Autor:
Tan, Shicheng1,2,3 (AUTHOR), Duan, Zhen1,2,3 (AUTHOR), Zhao, Shu1,2,3 (AUTHOR) zhaoshuzs2002@hotmail.com, Chen, Jie1,2,3 (AUTHOR), Zhang, Yanping1,2,3 (AUTHOR) zhangyp2@gmail.com
Publikováno v:
Information Retrieval Journal. Jun2021, Vol. 24 Issue 3, p175-204. 30p.