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Efficient knowledge graph to text powered by LLGM: linear latent graph model 期刊论文
COMPLEX & INTELLIGENT SYSTEMS, 2025, 卷号: 11, 期号: 8, 页码: 22
作者:  Zhao, Xiaokang;  Zheng, Yao;  Shan, Yubo;  Li, Jingyuan;  Zhang, Kun;  Wang, Yuanzhuo
收藏  |  浏览/下载：1/0  |  提交时间：2025/12/03
Knowledge graph to text generation  Linear attention  Low rank compression  Fourier network  
Retriever-generator-verification: A novel approach to enhancing factual coherence in open-domain question answering 期刊论文
INFORMATION PROCESSING & MANAGEMENT, 2025, 卷号: 62, 期号: 4, 页码: 16
作者:  Sun, Shiqi;  Zhang, Kun;  Li, Jingyuan;  Yu, Min;  Hou, Kun;  Wang, Yuanzhuo;  Cheng, Xueqi
收藏  |  浏览/下载：39/0  |  提交时间：2025/06/25
Question answering  Large language model  Information retrieval  In-context learning  
Burst-Sensitive Traffic Forecast via Multi-Property Personalized Fusion in Federated Learning 期刊论文
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2025, 卷号: 24, 期号: 7, 页码: 5598-5614
作者:  Xue, Jingjing;  Sun, Sheng;  Liu, Min;  Wang, Yuwei;  Meng, Xuying;  Wang, Jingyuan;  Zhang, JunBo;  Xu, Ke
收藏  |  浏览/下载：1/0  |  提交时间：2025/12/03
Predictive models  Forecasting  Data models  Market research  Fluctuations  Computational modeling  Training  Telecommunication traffic  Adaptation models  Mathematical models  Network traffic forecast  federated learning (FL)  heterogeneous data  multi-scale representation  personalized fusion  
Edge-centric optimization: a novel strategy for minimizing information loss in graph-to-text generation (vol 11, 74, 2025) 期刊论文
COMPLEX & INTELLIGENT SYSTEMS, 2025, 卷号: 11, 期号: 5, 页码: 1
作者:  Zheng, Yao;  Li, Jingyuan;  Cen, Jianhe;  Sun, Shiqi;  Yin, Dahu;  Wang, Yuanzhuo
收藏  |  浏览/下载：9/0  |  提交时间：2025/06/25
O-PRESS: Boosting OCT axial resolution with Prior guidance, Recurrence, and Equivariant Self-Supervision 期刊论文
MEDICAL IMAGE ANALYSIS, 2025, 卷号: 99, 页码: 16
作者:  Li, Kaiyan;  Yang, Jingyuan;  Liang, Wenxuan;  Li, Xingde;  Zhang, Chenxi;  Chen, Lulu;  Wu, Chan;  Zhang, Xiao;  Xu, Zhiyan;  Wang, Yueling;  Meng, Lihui;  Zhang, Yue;  Chen, Youxin;  Zhou, S. Kevin
收藏  |  浏览/下载：56/0  |  提交时间：2024/12/06
Retinal imaging  OCT image reconstruction  Resolution  Self-supervised learning  Prior guidance  
Edge-centric optimization: a novel strategy for minimizing information loss in graph-to-text generation 期刊论文
COMPLEX & INTELLIGENT SYSTEMS, 2025, 卷号: 11, 期号: 1, 页码: 19
作者:  Yao, Zheng;  Li, Jingyuan;  Cen, Jianhe;  Sun, Shiqi;  Yin, Dahu;  Wang, Yuanzhuo
收藏  |  浏览/下载：11/0  |  提交时间：2025/06/25
Graph-generated text  Knowledge representation  Knowledge graphs  Graph theory  Edge-aware attention  
A novel feature integration method for named entity recognition model in product titles 期刊论文
COMPUTATIONAL INTELLIGENCE, 2024, 卷号: 40, 期号: 3, 页码: 19
作者:  Sun, Shiqi;  Zhang, Kun;  Li, Jingyuan;  Sun, Xinghang;  Cen, Jianhe;  Wang, Yuanzhuo
收藏  |  浏览/下载：30/0  |  提交时间：2024/12/06
multitask learning  named entity recognition  natural language processing  
High Throughput Transcriptome Data Analysis and Computational Verification Reveal Immunotherapy Biomarkers of Compound Kushen Injection for Treating Triple-Negative Breast Cancer 期刊论文
FRONTIERS IN ONCOLOGY, 2021, 卷号: 11, 页码: 23
作者:  Liu, Xinkui;  Wu, Yang;  Zhang, Yingying;  Bu, Dechao;  Wu, Chao;  Lu, Shan;  Huang, Zhihong;  Song, Yurong;  Zhao, Yi;  Guo, Fengying;  Ye, Peizhi;  Fu, Changgeng;  Shen, Liangliang;  Zhang, Jingyuan;  Wang, Haojia;  Duan, Xianchun;  Wu, Jiarui
收藏  |  浏览/下载：62/0  |  提交时间：2022/06/21
compound kushen injection  triple-negative breast cancer  RNA sequencing  tumor microenvironment  prognostic signature  
NeuO: Exploiting the sentimental bias between ratings and reviews with neural networks 期刊论文
NEURAL NETWORKS, 2019, 卷号: 111, 页码: 77-88
作者:  Xu, Yuanbo;  Yang, Yongjian;  Han, Jiayu;  Wang, En;  Zhuang, Fuzhen;  Yang, Jingyuan;  Xiong, Hui
收藏  |  浏览/下载：302/0  |  提交时间：2019/04/03
Opinion bias  Recommender systems  Convolutional neural network  Dual attention vectors  
社交网络用户在在线媒体中点播行为预测 期刊论文
中文信息学报, 2017, 卷号: 31.0, 期号: 004, 页码: 199
作者:  刘强;  李静远;  王元卓;  刘悦;  任彦
收藏  |  浏览/下载：37/0  |  提交时间：2023/12/04
社交网络  在线媒体  用户偏好  预测