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Decoupled knowledge distillation method based on meta-learning

High-Confidence Computing 2024年第1期4卷 1-6页

作者： Wenqing Du Liting Geng Jianxiong Liu Zhigang Zhao Chunxiao Wang Jidong Huo Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science Center(National Supercomputer Center in Jinan)Qilu University of Technology(Shandong Academy of Sciences)Jinan 250014China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer ScienceJinan 250014China Aerospace Science&Industry Network Information Development Co. LTDBeijing 100854China

With the advancement of deep learning techniques,the number of model parameters has been increasing,leading to significant memory consumption and limits in the deployment of such models in real-time *** reduce the number of model parameters and enhance the generalization capability of neural networks,we propose a method called Decoupled MetaDistil,which involves decoupled *** method utilizes meta-learning to guide the teacher model and dynamically adjusts the knowledge transfer strategy based on feedback from the student model,thereby improving the generalization ***,we introduce a decoupled loss method to explicitly transfer positive sample knowledge and explore the potential of negative samples *** experiments demonstrate the effectiveness of our method.

关键词： Model compression Knowledge distillation Meta-learning Decoupled loss

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Malicious Client Detection with Differential Privacy Constraints Based on Model Update Slicing and K-Means Clustering 6

Malicious Client Detection with Differential Privacy Constra...

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6th International Conference on Frontier Technologies of information and computer, ICFTIC 2024

作者： Qi, Mengshi Wang, Xin He, Yunpeng Yang, Ming Wu, Xiaoming Key Laboratory of Computing Power Network and Information Security Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250014 China

ISBN: (纸本)9798331541750

Federated learning (FL) is a decentralized machine learning technique that protects data privacy by trainng models locally on devices and sharing only model updates instead of raw data. However, FL also faces multiple security challenges. Clientside poisoning attacks can compromise global model training by injecting malicious updates. Additionally, the server may infer private information from client model updates. Most existing studies address these two risks separately, lacking a systematic analysis and response to their combined threats. This paper proposes a method called Sliced-Clustering Guard (SCGuard), which slices gradients and performs clustering analysis on each segment, enabling the server to more accurately detect malicious updates and effectively differentiate malicious client updates with differential privacy (DP) protection. Experimental results demonstrate that SCGuard can mitigate poisoning attacks while effectively safeguarding clients' sensitive information. © 2024 IEEE.

关键词： Federated learning

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An Adaptive Residual Coordinate Attention-Based network for Hat and Mask Wearing Detection in Kitchen Environments

An Adaptive Residual Coordinate Attention-Based Network for ...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhao, Ying Wu, Xiaoming Liu, Xiangzhi Chen, Hao Qi, Bei Dong, Huomin Key Laboratory of Computing Power Network and Information Security Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9781665410205

In order to ensure food safety, it is required for personnel to wear hats and masks during food handling processes. To accurately detect the wearing status of kitchen staff, the ARP-YOLO model is proposed. Firstly, images are obtained from multiple kitchens and angles to construct a dataset reflecting the wearing status of hats and masks. To simulate more complex kitchen environments, Gaussian noise is added to the data and lighting conditions are adjusted for data augmentation. Lighting conditions in the kitchen can affect detection, causing the same target to exhibit different shapes and features under different lighting conditions, leading to missed detections. To address the above issues, we propose ARCA (Adaptive-Residual-Coordinate-Attention), which uses residual connections to strengthen attention to important features while preserving original features, and employs adaptive convolution reduction to reduce module parameters. To improve target localization accuracy, P2 detection layers are added in the Neck to obtain more accurate target position information. The ARP-YOLO model demonstrates significant improvements over the baseline model, with a 13.6% increase in Recall, allowing for more effective target capture and reduced missed detection risk. Additionally, mAP@0.5 has increased by 10%, enhancing target localization accuracy. The F1-Score has also increased by 7.4%, better balancing the relationship between Precision and Recall. To validate the effectiveness of the model, comparative experiments with other models are conducted, showing that ARP-YOLO model's Recall and Average Precision(AP) are higher than those of other models. © 2024 IEEE.

关键词： Lighting

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Code Generation From Flowcharts with Texts: A Benchmark Dataset and An Approach

Code Generation From Flowcharts with Texts: A Benchmark Data...

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2022 Findings of the Association for Computational Linguistics: EMNLP 2022

作者： Liu, Zejie Hu, Xiaoyu Zhou, Deyu Li, Lin Zhang, Xu Xiang, Yanzheng Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China Nanjing Origin Information Technology Company China

Currently, researchers focus on generating codes from the requirement documents. However, current approaches still perform poorly on some requirements needing complex problem-solving skills. In reality, to tackle such complex requirements, instead of directly translating requirement documents into codes, software engineers write codes via unified modeling language diagrams, such as flowcharts, an intermediate tool to analyze and visualize the system. Therefore, we propose a new source code generation task, that is, to generate source code from flowcharts with texts. We manually construct a benchmark dataset containing 320 flowcharts with their corresponding source codes. Obviously, it is not straightforward to employ the current approaches for the new source code generation task since (1) the flowchart is a graph that contains various structures, including loop, selection, and others which is different from texts;(2) the connections between nodes in the flowchart are abundant and diverse which need to be carefully handled. To solve the above problems, we propose a two-stage code generation model. In the first stage, a structure recognition model is employed to transform the flowchart into pseudo-code containing the structural conventions of a typical programming language such as while, if. In the second stage, a code generation model is employed to convert the pseudo-code into code. Experimental results show that the proposed approach can achieve some improvement over the baselines. © 2022 Association for Computational Linguistics.

关键词： Flowcharting

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A Sharding Scheme Based on Graph Partitioning Algorithm for Public Blockchain

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computer Modeling in Engineering & Sciences 2024年第6期139卷 3311-3327页

作者： Shujiang Xu Ziye Wang Lianhai Wang Miodrag J.Mihaljevi′c Shuhui Zhang Wei Shao Qizheng Wang Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science CenterQilu University of Technology(Shandong Academy of Sciences)Jinan250014China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer ScienceJinan250014China Mathematical Institute The Serbian Academy of Sciences and ArtsBelgrade11000Serbia

Blockchain technology,with its attributes of decentralization,immutability,and traceability,has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business ***,transaction performance and scalability has become the main challenges hindering the widespread adoption of *** to its inability to meet the demands of high-frequency trading,blockchain cannot be adopted in many *** improve the transaction capacity,researchers have proposed some on-chain scaling technologies,including lightning networks,directed acyclic graph technology,state channels,and shardingmechanisms,inwhich sharding emerges as a potential scaling ***,excessive cross-shard transactions and uneven shard workloads prevent the sharding mechanism from achieving the expected *** paper proposes a graphbased sharding scheme for public blockchain to efficiently balance the transaction *** crossshard transactions and evening-out workloads among shards,the scheme reduces transaction confirmation latency and enhances the transaction capacity of the ***,the scheme can achieve a high-frequency transaction as well as a better blockchain *** results show that the scheme effectively reduces the cross-shard transaction ratio to a range of 35%-56%and significantly decreases the transaction confirmation latency to 6 s in a blockchain with no more than 25 shards.

关键词： Blockchain sharding graph partitioning algorithm

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Person video alignment with human pose registration

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Frontiers of computer Science 2023年第4期17卷 229-231页

作者： Yu ZHANG Zihua WANG Jingyang ZHOU Siya MI School of Computer Science and Engineering and the Key Lab of Computer Network and Information Integration(Ministry of Education)Southeast UniversityNanjing 211189China School of Cyber Science and Engineering Southeast UniversityNanjing 211189China Purple Mountain Laboratories Nanjing 211111China

1 Introduction and main *** alignment,especially human action alignment,is a challenging *** purpose is to develop an algorithm to match the same process so that videos can be *** the progress that has been made in image recognition,it is still a difficult problem for distinguishing from similar frames for alignment without context information.

关键词： alignment video frames

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Universal and General Quantum Simultaneous Secret Distribution with Dense Coding by Using One-Dimensional High-Level Cluster States

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Journal of computer Science & Technology 2021年第1期36卷 221-230页

作者： Zhi-Hao Liu Han-Wu Chen School of Computer Science and Engineering Southeast UniversityNanjing 211189China Key Laboratory of Computer Network and Information Integration(Southeast University) Ministry of Education Nanjing 211189China

A universal and general quantum simultaneous secret distribution(QSSD)protocol is put forward based on the properties of the one-dimensional high-level cluster states,in which one sender dispatches different high-level classical secret messages to many users at the same *** to the idea of quantum dense coding,the sender can send different two-dit classical messages(two d-level classical numbers)to different receivers simultaneously by using a one-dimensional d-level cluster state,which means that the information capacity is up to the *** estimate the security of quantum channels,a new eavesdropping check strategy is put ***,a new attack model,the general individual attack is proposed and *** is shown that the new eavesdropping check strategy can effectively prevent the traditional attacks including the general individual *** addition,multiparty quantum secret report(MQSR,the same as quantum simultaneous secret submission(QSSS))in which different users submit their different messages to one user simultaneously can be gotten if the QSSD protocol is changed a little.

关键词： quantum simultaneous secret distribution(QSSD) multiparty quantum secret report(MQSR) quantum simultaneous secret submission(QSSS) quantum secret sharing quantum broadcast communication

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Neural network-Based State Estimation for Nonlinear Systems With Denial-of-Service Attack Under Try-Once-Discard Protocol

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IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2182-2184页

作者： Xueli Wang Shangwei Zhao Ming Yang Xin Wang Xiaoming Wu the Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science CenterQilu University of Technology(Shandong Academy of Sciences)Jinan 250014 Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer ScienceJinan 250014China Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China

Dear Editor,This letter deals with state estimation issues of discrete-time nonlinear systems subject to denial-of-service(DoS)attacks under the try-once-discard(TOD)*** specifically,to reduce the communication burden,a TOD protocol with novel update rules on protocol weights is designed for scheduling measurement *** addition,unknown nonlinear functions vulnerable to DoS attacks are considered due to the openness and vulnerability of the network.

关键词： Service DoS service

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Cross-chain Transaction Tracking Protocol based on Multi-dimensional Digital Watermarking Fingerprints 6

Cross-chain Transaction Tracking Protocol based on Multi-dim...

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6th International Conference on Frontier Technologies of information and computer, ICFTIC 2024

作者： Li, Duanzhen Xu, Shujiang He, Haochen Xue, Hongrui Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250014 China

ISBN: (纸本)9798331541750

Cross-chain technology plays a critical role in the process of interconnecting blockchains. However, all attention has been focused on how to achieve efficient cross-chain interoperability protocols, thus neglecting the most important security issues in cross-chain data interaction. Frequent network attacks and data privacy leaks have sounded the alarm for the safety of cross-chain data transactions. How to solve the problem of data ownership tracking in cross-chain transactions has become the top priority. This paper designs a cross-chain transaction tracking protocol based on multi-dimensional digital watermark fingerprints, using robust watermark, fragile watermark, and user identity key to achieve multi-dimensional tracking and supervision of cross-chain data transactions. Finally, this paper analyzes the feasibility and efficiency of the proposed protocol through experiments. © 2024 IEEE.

关键词： Blockchain

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Persuasion Should be Double-Blind: A Multi-Domain Dialogue Dataset With Faithfulness Based on Causal Theory of Mind

arXiv

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arXiv 2025年

作者： Zhang, Dingyi Zhou, Deyu School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China

Persuasive dialogue plays a pivotal role in human communication, influencing various domains. Recent persuasive dialogue datasets often fail to align with real-world interpersonal interactions, leading to unfaithful representations. For instance, unrealistic scenarios may arise, such as when the persuadee explicitly instructs the persuader on which persuasion strategies to employ, with each of the persuadee’s questions corresponding to a specific strategy for the persuader to follow. This issue can be attributed to a violation of the "Double Blind" condition, where critical information is fully shared between participants. In actual human interactions, however, key information—such as the mental state of the persuadee and the persuasion strategies of the persuader—is not directly accessible. The persuader must infer the persuadee’s mental state using Theory of Mind capabilities and construct arguments that align with the persuadee’s motivations. To address this gap, we introduce ToMMA, a novel multi-agent framework for dialogue generation that is guided by causal Theory of Mind. This framework ensures that information remains undisclosed between agents, preserving "double-blind" conditions, while causal ToM directs the persuader’s reasoning, enhancing alignment with human-like persuasion dynamics. Consequently, we present CToMPersu, a multi-domain, multi-turn persuasive dialogue dataset that tackles both double-blind and logical coherence issues, demonstrating superior performance across multiple metrics and achieving better alignment with real human dialogues. Our dataset and prompts are available at https://***/DingyiZhang/ToMMA-CToMPersu. Copyright © 2025, The Authors. All rights reserved.

关键词： Economic and social effects

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