检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Wang, Zhenglin Wu, Jialong Li, Pengfei Jiang, Yong Zhou, Deyu School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China Tongyi Lab Alibaba Group China

Temporal reasoning is fundamental to human cognition and is crucial for various real-world applications. While recent advances in Large Language Models have demonstrated promising capabilities in temporal reasoning, existing benchmarks primarily rely on rule-based construction, lack contextual depth, and involve a limited range of temporal entities. To address these limitations, we introduce Chinese Time Reasoning (CTM), a benchmark designed to evaluate LLMs on temporal reasoning within the extensive scope of Chinese dynastic chronology. CTM emphasizes cross-entity relationships, pairwise temporal alignment, and contextualized and culturally-grounded reasoning, providing a comprehensive evaluation. Extensive experimental results reveal the challenges posed by CTM and highlight potential avenues for improvement. Copyright © 2025, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Binary decomposition: a problem transformation perspective for open-set semi-supervised learning 24

Binary decomposition: a problem transformation perspective f...

引用

Proceedings of the 41st International Conference on Machine Learning

作者： Jun-Yi Hang Min-Ling Zhang School of Computer Science and Engineering Southeast University Nanjing China and Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China

Semi-supervised learning (SSL) is a classical machine learning paradigm dealing with labeled and unlabeled data. However, it often suffers performance degradation in real-world open-set scenarios, where unlabeled data contains outliers from novel categories that do not appear in labeled data. Existing studies commonly tackle this challenging open-set SSL problem with detect-and-filter strategy, which attempts to purify unlabeled data by detecting and filtering outliers. In this paper, we propose a novel binary decomposition strategy, which refrains from error-prone procedure of outlier detection by directly transforming the original open-set SSL problem into a number of standard binary SSL problems. Accordingly, a concise yet effective approach named BDMatch is presented. BDMatch confronts two attendant issues brought by binary decomposition, i.e. class-imbalance and representation-compromise, with adaptive logit adjustment and label-specific feature learning respectively. Comprehensive experiments on diversified benchmarks clearly validate the superiority of BDMatch as well as the effectiveness of our binary decomposition strategy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on long and short-term social recommendation based on convolutional and gated recurrent units 29

Research on long and short-term social recommendation based ...

引用

29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Jia, Zihe Xue, Peng Dai, Zhiqiang Gao, Qian Zhang, Xiaomeng Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250014 China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China

ISBN: (纸本)9798350330717

The development of the Internet has made people more closely related and has put forward higher requirements for recommendation models. Most recommendation models are studied only for the long-term interests of users. In this paper, the interaction time between the user and the item is introduced as auxiliary information in the model construction. Interaction time is used to determine users' long-term preferences and short-term preferences. In this paper, temporal features are extracted by building a convolutional gated recurrent unit with attention neural network (CNN-GRU-Attention). Firstly, for the problem of accurate feature extraction, CNN are constructed to extract higher-level and more abstract features of themselves and transform high-dimensional data into low-dimensional data;secondly, for the problem of social temporality, GRU are used to not only extract temporal information, but also effectively reduce gradient dispersion, making model convergence and training easier;finally, Graph Attention networks are used to aggregate the social relationship information of users and items respectively, which constitute the final feature representation of users and items respectively. In particular, a modified cosine similarity is used to reduce the error caused by data insensitivity when constructing the social information of the item. In this study, simulation experiments are conducted on two publicly available datasets (Epinions and Ciao), and the experimental results show that the proposed recommended model performs better than other social recommendation models, improving the evaluation metrics of MAE and RMSE by 1.06%-1.33% and 1.19%-1.37%, respectively. The effectiveness of the model innovation is proved. © 2023 IEEE.

关键词： convolutional gated recurrent unit graph attention networks neighborhood recommendation systems social networks

来源：评论

学校读者我要写书评

暂无评论

Multidimensional Voronoi Constellations vs. Short Blocklength Probabilistic Shaping: A Comparison for Multilevel Coding Approach

Multidimensional Voronoi Constellations vs. Short Blocklengt...

引用

2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on information Photonics and Optical Communications, IPOC 2024

作者： Sheng, Yajie Chen, Bin Lei, Yi Deng, Jingxin Xu, Jiwei Fu, Mengfan Zhuge, Qunbi Li, Shen Department of Computer Science and Information Engineering Hefei University of Technology Hefei China State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China Department of Electrical and Computer Engineering Université Laval Québec Canada

Performance of concatenated multilevel coding with probabilistic shaping (PS) and Voronoi constellations (VCs) is analysed over AWGN channel. Numerical results show that VCs provide up to 1.3 dB SNR gains over PS-QAM ... 详细信息

ISBN: (纸本)9798350379266

关键词： Probability distributions

来源：评论

学校读者我要写书评

暂无评论

Low-profile metamaterial with ultra-wide band ratio based on active frequency selective surfaces

引用

Optics Express 2025年第7期33卷 15901-15916页

作者： Xu, Ruize Ren, Peng Li, Yi Gu, Chao Xu, Baoyi Xue, Wei Wang, Minrui Xiang, Zheng State Key Laboratory of Integrated Services Networks Xidian University No. 2 South Taibai Road Xi’an710071 China Centre for Wireless Innovation School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast BelfastBT3 9DT United Kingdom School of Electronics and Information Northwestern Polytechnical University Xi’an710072 China

This paper presents a low-profile metamaterial with ultra-wide band ratio (BR) based on active frequency selective surfaces (AFSSs) to overcome the limited tuning range and suboptimal profile of current designs. The proposed design consists of a periodic pattern printed on the top of a thin substrate and a bias network on the bottom, with varactor diodes symmetrically integrated into the top metal layer. Based on the equivalent circuit model, the mechanism of wideband tuning is analyzed theoretically. The corresponding simulation results indicate that the designed AFSS can achieve a large tuning range for the first operating band from 1.12 to 7.86 GHz while maintaining stability in the second operating band. This allows for a continuous variation from a small BR to a large BR, with a tuning range reaching 601.79%. To the best of the authors’ knowledge, this is the first time that the concept of band ratio range (BRR) has been proposed to characterize the level of BR variation. Considering the feasibility of fabrication and limitations due to the tuning range of a single commercially available varactor diode, measurements were performed based on two fabricated prototypes. The simulation results are consistent with the experimental results. Compared with existing literature, the proposed AFSS can provide significant advantages such as good angular stability, polarization insensitivity, miniaturization, and ultra-wideband tunability. Our design is applicable to controlling the propagation of electromagnetic waves in various communication systems and is well-suited for electromagnetic shielding in communication devices or optical devices across different frequency bands. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Electromagnetic shielding

来源：评论

学校读者我要写书评

暂无评论

RankMatch: A Novel Approach to Semi-Supervised Label Distribution Learning Leveraging Inter-label Correlations

arXiv

引用

arXiv 2023年

作者： Kou, Zhiqiang Xie, Yucheng Wang, Jing Jia, Yuheng Shi, Boyu Geng, Xin MOE Key Laboratory of Computer Network and Information Integration School of Computer Science and Engineering Southeast University Nanjing China

This paper introduces RankMatch, an innovative approach for Semi-Supervised Label Distribution Learning (SSLDL). Addressing the challenge of limited labeled data, RankMatch effectively utilizes a small number of labeled examples in conjunction with a larger quantity of unlabeled data, reducing the need for extensive manual labeling in Deep Neural Network (DNN) applications. Specifically, RankMatch introduces an ensemble learning-inspired averaging strategy that creates a pseudo-label distribution from multiple weakly augmented images. This not only stabilizes predictions but also enhances the model’s robustness. Beyond this, RankMatch integrates a pairwise relevance ranking (PRR) loss, capturing the complex inter-label correlations and ensuring that the predicted label distributions align with the ground truth. We establish a theoretical generalization bound for RankMatch, and through extensive experiments, demonstrate its superiority in performance against existing SSLDL methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

PROMIPL: A Probabilistic Generative Model for Multi-Instance Partial-Label Learning

PROMIPL: A Probabilistic Generative Model for Multi-Instance...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Yin-Fang Yang Wei Tang Min-Ling Zhang School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of Computer Network Information Integration (Southeast University) Ministry of Education China

ISBN: (数字)9798331506681

ISBN: (纸本)9798331506698

Multi-instance partial-label learning (MIPL) tackles scenarios where each training sample is represented as a multiinstance bag associated with a candidate label set. This set contains one true label and several false positives. Existing MIPL algorithms have predominantly focused on mapping multiinstance bags to candidate label sets for disambiguation. However, these algorithms may not be adequately generalizable in intricate real-world situations due to their reliance on heuristic methods for identifying true labels. In this paper, we propose PROMIPL, i.e., a PRObabilistic generative model for Multi-instance partiallabel learning, to address these challenges. PROMIPL is the first attempt to explore the probabilistic generative model to infer latent ground-truth labeling information from the data generation process in multi-instance partial-label learning. Besides, the discovered underlying structures also provide improved explanations of the classification predictions. To circumvent the computationally intensive process of training the generative model, we formulate a unified variational lower bound within the stochastic gradient variational Bayesian framework for the model parameters. Experimental results from benchmark and realworld datasets show that our proposed PROMIPL is competitive or superior to the state-of-the-art methods.

关键词： Training Lower bound Computational modeling Heuristic algorithms Stochastic processes Probabilistic logic Data models Bayes methods Labeling Data mining

来源：评论

学校读者我要写书评

暂无评论

Verifier-local revocation group signatures with backward unlinkability from lattices

引用

Frontiers of information Technology & Electronic Engineering 2022年第6期23卷 876-892页

作者： Yanhua ZHANG Ximeng LIU Yupu HU Yong GAN Huiwen JIA College of Computer and Communication Engineering Zhengzhou University of Light IndustryZhengzhou 450001China College of Mathematics and Computer Science Fuzhou UniversityFuzhou 350108China Stale Key Laboratory of Integrated Service Networks Xidian UniversityXi’an 710071China College of Information Engineering Zhengzhou University of TechnologyZhengzhou 450044China School of Mathematics and Information Science Guangzhou UniversityGuangzhou 510006China

For group signature(GS)supporting membership revocation,verifier-local revocation(VLR)mechanism seems to be a more flexible choice,because it requires only that verifiers download up-to-date revocation information for signature verification,and the signers are not *** a post-quantum secure cryptographic counterpart of classical number-theoretic cryptographic constructions,the first lattice-based VLR group signature(VLR-GS)was introduced by Langlois et al.(2014).However,none of the contemporary lattice-based VLR-GS schemes provide backward unlinkability(BU),which is an important property to ensure that previously issued signatures remain anonymous and unlinkable even after the corresponding signer(i.e.,member)is *** this study,we introduce the first lattice-based VLR-GS scheme with BU security(VLR-GS-BU),and thus resolve a prominent open problem posed by previous *** new scheme enjoys an O(log N)factor saving for bit-sizes of the group public-key(GPK)and the member’s signing secret-key,and it is free of any public-key *** the random oracle model,our scheme is proven secure under two well-known hardness assumptions of the short integer solution(SIS)problem and learning with errors(LWE)problem.

关键词： Group signature Lattice-based cryptography Verifier-local revocation Backward unlikability Short integer solution

来源：评论

学校读者我要写书评

暂无评论

NL2SQL Enhancement through Semantic Representation Aggregation 5

NL2SQL Enhancement through Semantic Representation Aggregati...

引用

5th International Conference on computer information Science and Application Technology, CISAT 2022

作者： Long, Lingli Zhu, Yongjin Shao, Jun Kong, Zheng Li, Jian Liu, Zejie Zhang, Xu Jiangsu Frontier Electric Technology Co. Ltd. China School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China

ISBN: (纸本)9781510660076

Natural Language to SQL (NL2SQL) is a technology that converts natural language into executable SQL statements. For single table tasks, the dominant approach is a slot-filling-based model which actually performs multi-objective prediction. However, in existing multi-objective models, it is difficult to optimize multiple objectives simultaneously. Low correlation or conflict between various objectives can result in the model not being able to learn the parameters effectively. To effectively address this problem, this paper considers redesigning the sharing mechanism between multiple tasks and the specific network structure of individual tasks through a semantic aggregation approach in order to alleviate the above phenomenon. © 2022 SPIE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

An Efficient Direct Downlink Sensing Method Using 5G NR SSB Signals in Perceptive Mobile networks

引用

IEEE Internet of Things Journal 2025年第11期12卷 15360-15369页

作者： Li, Hang Xiang, Yang Guo, Qinghua Liu, Lizhe Huang, Xiaojing Cheng, Zhiqun Pang, Yashan Hangzhou Dianzi University School of Electronics and Information Hangzhou310018 China Academy of Network and Communications of CETC National Key Laboratory of Advanced Communication Networks Hebei Shijiazhuang050081 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia University of Technology Sydney Global Big Data Technologies Centre UltimoNSW2007 Australia

In perceptive mobile networks (PMNs), using 5G new radio (NR) signals for direct sensing poses a significant challenge to practical implementation due to the high computational complexity involved in estimating sensing parameters. In this article, an efficient sensing method is proposed to incorporate both downlink active sensing and passive sensing to estimate multiple sensing parameters, including delays, Angle of Arrival (AoA), Angle of Departure (AoD), and Doppler. In particular, it exploits the synchronization signal blocks (SSBs) to facilitate sensing with multiple remote radio units (RRUs). To reduce the computational complexity of direct sensing, a sparse model is developed to decouple multiple sensing parameter estimation, enabling efficient sensing method design. Then, leveraging unitary approximate message passing (UAMP) and sparse Bayesian learning (SBL), we propose an efficient method to achieve parameter estimation and association with corresponding RRUs. This method is further extended to general scenarios involving multiple path components with the same delay. Extensive simulations demonstrate the effectiveness of the proposed method, showing that it outperforms the existing ones in terms of sensing accuracy and complexity. © 2014 IEEE.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：