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REPRESENTATION: 作品数：930被引量：1111H指数：13; 导出分析报告; 相关作者：徐亮孙正兴张福炎熊洪允郝永华更多>>; 相关机构：中国科学院大学浙江大学西安外国语大学华中师范大学更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金国家重点基础研究发展计划国家教育部博士点基金国家高技术研究发展计划更多>>

Causal Representation Enhances Cross-Domain Named Entity Recognition in Large Language Models: 《Computers, Materials & Continua》2025年第5期2809-2828,共20页Jiahao Wu Jinzhong Xu Xiaoming Liu Guan Yang Jie Liu; supported by National Natural Science Foundation of China Joint Fund for Enterprise Innovation Development(U23B2029);National Natural Science Foundation of China(62076167,61772020);Key Scientific Research Project of Higher Education Institutions in Henan Province(24A520058,24A520060,23A520022);Postgraduate Education Reform and Quality Improvement Project of Henan Province(YJS2024AL053).; Large language models cross-domain named entity recognition task in the face of the scarcity of large language labeled data in a specific domain,due to the entity bias arising from the variation of entity information ...; 关键词：Large language model entity bias causal graph structure

Learning Hierarchical Adaptive Code Clouds for Neural 3D Shape Representation: 《Machine Intelligence Research》2025年第2期304-323,共20页Yuanxun Lu Xinya Ji Hao Zhu Xun Cao; supported by the National Natural Science Foundation of China(Nos.62001213 and 62025108).; Neural implicit representation(NIR)has attracted significant attention in 3D shape representation for its efficiency,generalizability,and flexibility compared with traditional explicit representations.Previous works u...; 关键词：Representation learning shape analysis deep implicit function 3D reconstruction 3D modeling

Efficient Parameterization for Knowledge Graph Embedding Using Hierarchical Attention Network: 《Computers, Materials & Continua》2025年第3期4287-4300,共14页Zhen-Yu Chen Feng-Chi Liu Xin Wang Cheng-Hsiung Lee Ching-Sheng Lin; supported by the National Science and Technology Council(NSTC),Taiwan,under Grants Numbers 112-2622-E-029-009 and 112-2221-E-029-019.; In the domain of knowledge graph embedding,conventional approaches typically transform entities and relations into continuous vector spaces.However,parameter efficiency becomes increasingly crucial when dealing with l...; 关键词：Knowledge graph embedding parameter efficiency representation learning reserved entity and relation sets hierarchical attention network

Multi-Scale Feature Fusion and Advanced Representation Learning for Multi Label Image Classification: 《Computers, Materials & Continua》2025年第3期5285-5306,共22页Naikang Zhong Xiao Lin Wen Du Jin Shi; supported by the National Natural Science Foundation of China(62302167,62477013);Natural Science Foundation of Shanghai(No.24ZR1456100);Science and Technology Commission of Shanghai Municipality(No.24DZ2305900);the Shanghai Municipal Special Fund for Promoting High-Quality Development of Industries(2211106).; Multi-label image classification is a challenging task due to the diverse sizes and complex backgrounds of objects in images.Obtaining class-specific precise representations at different scales is a key aspect of feat...; 关键词：Image classification MULTI-LABEL multi scale attention mechanisms feature fusion

Hybrid mesh-neural representation for 3D transparent object reconstruction: 《Computational Visual Media》2025年第1期123-140,共18页Jiamin Xu Zihan Zhu Hujun Bao Weiwei Xu; supported by“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2023C01181);supported by National Natural Science Foundation of China(No.62302134);Zhejiang Provincial Natural Science Foundation(No.LQ24F020031);supported by Information Technology Center and State Key Lab of CAD&CG,Zhejiang University.; In this study,we propose a novel method to reconstruct the 3D shapes of transparent objects using images captured by handheld cameras under natural lighting conditions.It combines the advantages of an explicit mesh an...; 关键词：transparent object 3D reconstruction environment matting neural rendering

FDCPNet:feature discrimination and context propagation network for 3D shape representation: 《虚拟现实与智能硬件(中英文)》2025年第1期83-94,共12页Weimin SHI Yuan XIONG Qianwen WANG Han JIANG Zhong ZHOU; Supported by the National Key R&D Program of China(2022YFC3803600).; Background Three-dimensional(3D)shape representation using mesh data is essential in various applications,such as virtual reality and simulation technologies.Current methods for extracting features from mesh edges or ...; 关键词：3D shape representation Mesh model MeshNet Feature discrimination Context propagation

Knowledge Graph Completion Method of Combining Structural Information with Semantic Information: 《Chinese Journal of Electronics》2024年第6期1412-1420,共9页Binhao HU Jianpeng ZHANG Hongchang CHEN; supported by the National Natural Science Foundation of China(Grant No.62002384);the General Project of China Postdoctoral Science Foundation(Grant No.2020M683760);the Songshan Laboratory Project(Grant No.221100210700-03)。; With the development of knowledge graphs,a series of applications based on knowledge graphs have emerged.The incompleteness of knowledge graphs makes the effect of the downstream applications affected by the quality o...; 关键词：Knowledge graph Knowledge graph completion Representation learning

A general tail item representation enhancement framework for sequential recommendation被引量：1: 《Frontiers of Computer Science》2024年第6期137-148,共12页Mingyue CHENG Qi LIU Wenyu ZHANG Zhiding LIU Hongke ZHAO Enhong CHEN; the National Key R&D Program of China(No.2021YFF0901003)。; Recently advancements in deep learning models have significantly facilitated the development of sequential recommender systems(SRS).However,the current deep model structures are limited in their ability to learn high-...; 关键词：sequential recommendation long-tail distribution training accelerating

Representation strategy for unsupervised domain adaptation on person re-identification: 《Optoelectronics Letters》2024年第12期749-756,共8页LI Hao ZHANG Tao LI Shuang LI Xuan ZHAO Xin; The task of unsupervised person re-identification(Re-ID)is to transfer the knowledge learned in the source domain with no labels to the target domain with no labels.Due to the significant differences in the background...; 关键词：NETWORKS branch branching

Position-Aware and Subgraph Enhanced Dynamic Graph Contrastive Learning on Discrete-Time Dynamic Graph: 《Computers, Materials & Continua》2024年第11期2895-2909,共15页Jian Feng Tian Liu Cailing Du; Unsupervised learning methods such as graph contrastive learning have been used for dynamic graph represen-tation learning to eliminate the dependence of labels.However,existing studies neglect positional information ...; 关键词：Dynamic graph representation learning graph contrastive learning structure representation position representation evolving pattern

REPRESENTATION