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31st International Conference on Computational Linguistics, COLING 2025

作者： Tang, Jingyao Li, Lishuang Mi, Liteng Wu, Haiming Lu, Hongbin School of Computer Science and Technology Dalian University of Technology China School of Computer Science and Technology Beijing Institute of Technology China School of Computer Science and Artificial Intelligence Liaoning Normal University China

ISBN: (纸本)9798891761964

Zero-shot event-relational reasoning is an important task in natural language processing, and existing methods jointly learn a variety of event-relational prefixes and inference-form prefixes to achieve such tasks. However, training prefixes consumes large computational resources and lacks interpretability. Additionally, learning various relational and inferential knowledge inefficiently exploits the connections between tasks. Therefore, we first propose a method for Reasoning-Oriented Locating and Editing (ROLE), which locates and edits the key modules of the language model for reasoning about event relations, enhancing interpretability and also resource-efficiently optimizing the reasoning ability. Subsequently, we propose a method for Analogy-Based Locating and Editing (ABLE), which efficiently exploits the similarities and differences between tasks to optimize the zero-shot reasoning capability. Experimental results show that ROLE improves interpretability and reasoning performance with reduced computational cost. ABLE achieves SOTA results in zero-shot reasoning. © 2025 Association for Computational Linguistics.

关键词： Zero-shot learning

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A Pre-Selection-Based Ant Colony System for Integrated Resources Scheduling Problem at Marine Container Terminal

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computers, Materials & Continua 2024年第8期80卷 2363-2385页

作者： Rong Wang Xinxin Xu Zijia Wang Fei Ji Nankun Mu School of Electronic and Information Engineering South China University of TechnologyGuangzhou510641China School of Computer Science and Technology Ocean University of ChinaQingdao266100China School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou510006China School of Computer Science Chongqing UniversityChongqing400044China

Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics ***,the efficiency of resource scheduling significantly influences the operation performance of *** solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm ***,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated *** new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the ***,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection *** the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible *** the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality *** evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is *** results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.

关键词： Resource scheduling problem(RSP) ant colony system(ACS) marine container terminal(MCT) pre-selection strategy

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Finite-Time Sliding Mode Control of Vehicle Formation with Specified Performance

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Engineering Letters 2025年第3期33卷 620-629页

作者： Guo, Dongyang Zhang, Zhao Zhou, Hongyan Chen, Xue-Bo School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China

The current urban intelligent transportation is in a rapid development stage, and coherence control of vehicle formations has important implications in urban intelligent transportation research. This article focuses on the problem of urban intelligent transportation planning, and proposes a new control method for vehicle formation regulation tracking performance control with bounded disturbances and model uncertainty, combining the multiple advantages of sliding mode control and finite time control and utilizing the universal approximation of neural network. This method can ensure that the vehicle formation can achieve the specified tracking performance and be stable in finite time instead of asymptotically stable. First, the third-order dynamics model and spacing strategy of the vehicle are given. The tracking performance of the vehicle formation is specified. Then, the control objective of the system is transformed by using the error transformation to obtain a new system. An improved sliding mode surface is designed for the transformed system. Furthermore, the universal approximation property of the neural network is utilised to overcome the parameter uncertainty in the system. The reconstruction error of neural network is handled by a robust term. In addition, the jittery vibration phenomenon of sliding mode control has been overcome. Finally, the finite-time stability of the system is analysed by constructing the Lyapunov function, simulations were performed to validate and compare with conventional control methods, simulation results show that the novel control method proposed in this paper is significantly faster than the conventional control method, validated the effectiveness of the method proposed in this paper. © 2025, International Association of Engineers. All rights reserved.

关键词： Lyapunov functions

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A Hybrid Entropy and Blockchain Approach for Network Security Defense in SDN-Based IIoT

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Chinese Journal of Electronics 2023年第3期32卷 531-541页

作者： SU Jian JIANG Mengnan School of Computer Science Nanjing University of Information Science and Technology

In the industrial Internet of things(IIoT), various applications generate a large number of interactions and are vulnerable to various attacks, which are difficult to be monitored in a sophisticated way by traditional network architectures. Therefore, deploying software-defined network(SDN) in IIoT is essential to defend against various attacks. However, SDN has a drawback: there is a security problem of distributed denial-ofservice(DDoS) attacks at the control layer. This paper proposes an effective solution: DDoS detection within the domain using tri-entropy in information theory. The detected attacks are then uploaded to a smart contract in the blockchain, so that the attacks can be quickly cut off even if the same attack occurs in different domains. Experimental validation was conducted under different attack strengths and multiple identical attacks, and the results show that the method has better detection ability under different attack strengths and can quickly block the same attacks.

关键词： Smart contracts Network security Network architecture Denial-of-service attack Entropy Blockchains Software defined networking

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A Blockchain and CP-ABE Based Access Control Scheme with Fine-Grained Revocation of Attributes in Cloud Health

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computers, Materials & Continua 2024年第2期78卷 2787-2811页

作者： Ye Lu Tao Feng Chunyan Liu Wenbo Zhang School of Computer&Communication Lanzhou University of TechnologyLanzhou730000China School of Economics&Management Lanzhou University of TechnologyLanzhou730000China School of Computer Science Baoji University of Arts and ScienceBaoji721000China

The Access control scheme is an effective method to protect user data *** access control scheme based on blockchain and ciphertext policy attribute encryption(CP–ABE)can solve the problems of single—point of failure and lack of trust in the centralized ***,it also brings new problems to the health information in the cloud storage environment,such as attribute leakage,low consensus efficiency,complex permission updates,and so *** paper proposes an access control scheme with fine-grained attribute revocation,keyword search,and traceability of the attribute private key distribution *** technology tracks the authorization of attribute private *** credit scoring method improves the Raft protocol in consensus ***,the interplanetary file system(IPFS)addresses the capacity deficit of *** the premise of hiding policy,the research proposes a fine-grained access control method based on users,user attributes,and file *** optimizes the data-sharing *** the same time,Proxy Re-Encryption(PRE)technology is used to update the access *** proposed scheme proved to be *** analysis and experimental results show that the proposed scheme has higher efficiency and more *** can meet the needs of medical institutions.

关键词： Blockchain access-control CP-ABE cloud health

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DGECN++: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimation via Attention Mechanism

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IEEE Transactions on Circuits and Systems for Video technology 2024年第6期34卷 4214-4228页

作者： Cao, Tuo Zhang, Wenxiao Fu, Yanping Zheng, Shengjie Luo, Fei Xiao, Chunxia Wuhan University School of Computer Science Wuhan430072 China Anhui University School of Computer Science and Technology Hefei230039 China

Monocular object 6D pose estimation is a fundamental yet challenging task in computer vision. Recently, deep learning has been proven to be capable of predicting remarkable results in this task. Existing works often adopt a two-stage pipeline with establishing 2D-3D correspondences and utilizing a PnP/RANSAC or differentiable PnP algorithm to recover 6 degrees-of-freedom (6DoF) pose parameters. However, most of them hardly consider the geometric features in 3D space, and ignore the topological cues when performing differentiable PnP algorithms. To this end, we present an improved end-to-end monocular 6D pose estimation method (DGECN++) that incorporates depth estimation and a geometric-aware learnable PnP network. Our method is based on keypoints. First we detect the 2D keypoints that correspond to the 3D model. We then integrate differentiable PnP/RANSAC algorithm to create an end-to-end pipeline for 6D pose estimation. We focuses on the following three key aspects: 1) We utilize the estimated depth information to guide the process of extracting 2D-3D correspondences and refine the results using a cascaded differentiable PnP/RANSAC algorithm that incorporates geometric information. 2) We leverage the uncertainty of the estimated depth map to enhance the accuracy and robustness of the predicted 6D pose. 3) We propose a differentiable Perspective-n-Point (PnP) algorithm based on edge convolution and self-attention to explore the topological relationships between 2D-3D correspondences. Experimental results demonstrate that our proposed network surpasses existing methods in terms of both effectiveness and efficiency. © 1991-2012 IEEE.

关键词： Uncertainty analysis

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An Improved Iterated Greedy Algorithm for Solving Rescue Robot Path Planning Problem with Limited Survival Time

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computers, Materials & Continua 2024年第7期80卷 931-947页

作者： Xiaoqing Wang Peng Duan Leilei Meng Kaidong Yang School of Computer Science Liaocheng UniversityLiaocheng252000China Shandong Key Laboratory of Optical Communication Science and Technology School of Physics Science and Information TechnologyLiaocheng UniversityLiaocheng252059China

Effective path planning is crucial for mobile robots to quickly reach rescue destination and complete rescue tasks in a post-disaster *** this study,we investigated the post-disaster rescue path planning problem and modeled this problem as a variant of the travel salesman problem(TSP)with life-strength *** address this problem,we proposed an improved iterated greedy(IIG)***,a push-forward insertion heuristic(PFIH)strategy was employed to generate a high-quality initial ***,a greedy-based insertion strategy was designed and used in the destruction-construction stage to increase the algorithm’s exploration ***,three problem-specific swap operators were developed to improve the algorithm’s exploitation ***,an improved simulated annealing(SA)strategy was used as an acceptance criterion to effectively prevent the algorithm from falling into local *** verify the effectiveness of the proposed algorithm,the Solomon dataset was extended to generate 27 instances for ***,the proposed IIG was compared with five state-of-the-art *** parameter analysiswas conducted using the design of experiments(DOE)Taguchi method,and the effectiveness analysis of each component has been verified one by *** results indicate that IIGoutperforms the compared algorithms in terms of the number of rescue survivors and convergence speed,proving the effectiveness of the proposed algorithm.

关键词： Rescue robot path planning life strength improved iterative greedy algorithm problem-specific swap operators

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A Review of Intelligent Configuration and Its Security for Complex Networks

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Chinese Journal of Electronics 2024年第4期33卷 920-947页

作者： Yue ZHAO Bin YANG Fei TENG Xianhua NIU Ning HU Bo TIAN Science and Technology on Communication Security Laboratory School of Computer and Information Engineering Chuzhou University School of Computing and Artificial Intelligence Southwest Jiaotong University School of Computer and Software Engineering Xihua University Cyberspace Institute of Advanced Technology Guangzhou University

Complex networks are becoming more complex because of the use of many components with diverse technologies. In fact, manual configuration that makes each component interoperable has breed latent danger to system security. There is still no comprehensive review of these studies and prospects for further research. According to the complexity of component configuration and difficulty of security assurance in typical complex networks, this paper systematically reviews the abstract models and formal analysis methods required for intelligent configuration of complex networks, specifically analyzes, and compares the current key technologies such as configuration semantic awareness, automatic generation of security configuration, dynamic deployment, and verification evaluation. These technologies can effectively improve the security of complex networks intelligent configuration and reduce the complexity of operation and maintenance. This paper also summarizes the mainstream construction methods of complex networks configuration and its security test environment and detection index system, which lays a theoretical foundation for the formation of the comprehensive effectiveness verification capability of configuration security. The whole lifecycle management system of configuration security process proposed in this paper provides an important technical reference for reducing the complexity of network operation and maintenance and improving network security.

关键词： Complex networks Intelligent configuration Configuration security Software defined network Lifecycle management

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A decentralised asynchronous federated learning framework for autonomous driving

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International Journal of Vehicle Autonomous Systems 2024年第3-4期17卷 133-149页

作者： Li, Xiaoli Cai, Ting Xiong, Wei Xu, Degang Computer School HuBei University of Arts and Science Xiangyang China School of Computer Science and Engineering Hubei University of Technology Wuhan China

Traditional autonomous driving usually requires a large number of vehicles to upload data to a central server for training. However, collecting data from vehicles may violate personal privacy as road environmental information contains geographic location. Federated learning can achieve multi-vehicle collaborative sensing of the road environment while protecting data privacy. However, the existing centralised federated learning architecture faces some challenges, such as credibility, fairness, and real-time. To address the above issues, we propose a decentralised asynchronous federated learning framework based on blockchain. Firstly, using blockchain to replace the central server of traditional federated learning architecture avoids the untrustworthy issues caused by the central architecture. Secondly, the blockchain module includes scoring contract units and incentive contract units to prevent malicious vehicle attacks and designs fair incentive mechanisms to ensure the ecological health and sustainable development of federated learning. Thirdly, using the asynchronous federated learning algorithm, blockchain can immediately aggregate model updates from vehicles, greatly improving the overall training flexibility and real-time performance. Experimental results demonstrate the effectiveness of the proposed framework. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Adversarial machine learning

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A survey on cross-user federated recommendation

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science China(Information sciences) 2025年第4期68卷 7-32页

作者： Enyue YANG Yudi XIONG Wei YUAN Weike PAN Qiang YANG Zhong MING College of Computer Science and Software Engineering Shenzhen University School of Electrical Engineering and Computer Science The University of Queensland WeBank AI Lab WeBank Department of Computer Science and Engineering Hong Kong University of Science and Technology College of Big Data and Internet Shenzhen Technology University Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)

Recommender systems are effective in mitigating information overload, yet the centralized storage of user data raises significant privacy concerns. Cross-user federated recommendation(CUFR) provides a promising distributed paradigm to address these concerns by enabling privacy-preserving recommendations directly on user devices. In this survey, we review and categorize current progress in CUFR, focusing on four key aspects: privacy, security, accuracy, and efficiency. Firstly,we conduct an in-depth privacy analysis, discuss various cases of privacy leakage, and then review recent methods for privacy protection. Secondly, we analyze security concerns and review recent methods for untargeted and targeted *** untargeted attack methods, we categorize them into data poisoning attack methods and parameter poisoning attack methods. For targeted attack methods, we categorize them into user-based methods and item-based methods. Thirdly,we provide an overview of the federated variants of some representative methods, and then review the recent methods for improving accuracy from two categories: data heterogeneity and high-order information. Fourthly, we review recent methods for improving training efficiency from two categories: client sampling and model compression. Finally, we conclude this survey and explore some potential future research topics in CUFR.

关键词： cross-user federated recommendation federated recommendation federated learning recommender systems user privacy

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