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31st International Conference on Computational Linguistics, COLING 2025

作者： Liu, Xinjing Li, Ruifan Ye, Shuqin Zhang, Guangwei Wang, Xiaojie School of Artificial Intelligence Beijing University of Posts and Telecommunications China School of Computer Science Beijing University of Posts and Telecommunications China Engineering Research Center of Information Networks Ministry of Education China Key Laboratory of Interactive Technology and Experience System Ministry of Culture and Tourism China

ISBN: (纸本)9798891761964

Multimodal Aspect-Based Sentiment Analysis (MABSA) aims to extract aspect terms from text-image pairs and identify their sentiments. Previous methods are based on the premise that the image contains the objects referred by the aspects within the text. However, this condition cannot always be met, resulting in a suboptimal performance. In this paper, we propose COnditional Relation based Sentiment Analysis framework (CORSA). Specifically, we design a conditional relation detector (CRD) to mitigate the impact of the unmet conditional image. Moreover, we design a visual object localizer (VOL) to locate the exact condition-related visual regions associated with the aspects. With CRD and VOL, our CORSA framework takes a multi-task form. In addition, to effectively learn CORSA we conduct two types of annotations. One is the conditional relation using a pretrained referring expression comprehension model;the other is the bounding boxes of visual objects by a pretrained object detection model. Experiments on our built C-MABSA dataset show that CORSA consistently outperforms existing methods. The code and data are available at https://***/Liuxj-Anya/CORSA. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Transfer learning with a spatiotemporal graph convolution network for city flowprediction

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Frontiers of Information Technology & Electronic Engineering 2025年第1期26卷 79-92页

作者： Binkun LIU Yu KANG Yang CAO Yunbo ZHAO Zhenyi XU Department of Automation University of Science and Technology of ChinaHefei 230026China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China Institute of Advanced Technology University of Science and Technology of ChinaHefei 230088China

Recently,deep learning based city flow prediction has been extensively used in the establishment of *** methods are data-hungry,making them unscalable to areas lacking *** transfer learningcan use data-rich source domains to assist target domain cities in city flow prediction,the performance of existingmethods cannot meet the needs of actual use,because the long-distance road network connectivity is *** this problem,we propose a transfer learning method based on spatiotemporal graph convolution,in which weconstruct a co-occurrence space between the source and target domains,and then align the mapping of the sourceand target domains’data in this space,to achieve the transfer learning of the source city flow prediction modelon the target ***,a dynamic spatiotemporal graph convolution module along with a temporalencoder is devised to simultaneously capture the concurrent spatiotemporal features,which implies the inherentrelationship among the road network structures,human travel habits,and city bike ***,these concurrentfeatures are leveraged as cross-city invariant representations and nonlinearly spanned to a co-occurrence *** domain features are thereby aligned with the source domain features in the co-occurrence space by using aMahalanobis distance loss,to achieve cross-city bike flow *** proposed method is evaluated on the publicbike flow datasets in Chicago,New York,and Washington in 2015,and significantly outperforms state-of-the-arttechniques.

关键词： Transfer learning City flow prediction Spatiotemporal graph convolution

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A Game Theoretical Analysis of Voluntary Mask Wearing for Epidemic Spreading Over complex Networks

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Dynamic Games and Applications 2025年 1-23页

作者： Pei, Shan Xu, Fei Zhang, Boyu Laboratory of Mathematics and Complex Systems Ministry of Education School of Mathematical Sciences Beijing Normal University Beijing 100875 China State Key Laboratory of Remote Sensing Science Center for Global Change and Public Health College of Global Change and Earth System Science Beijing Normal University Beijing 100875 China Department of Mathematics Wilfrid Laurier University Waterloo N2L 3C5 ON Canada

In this paper, we propose a network evolutionary game model to study the coevolution of mask-wearing behavior and epidemic spreading over complex networks. By applying mean-field and pairwise approximations, we transform the stochastic coevolutionary process into a system of ordinary differential equations and derive the strategy dynamics and state dynamics. We show that in a stable equilibrium of the strategy dynamics, infected individuals do not wear masks, and susceptible individuals wear masks only if both the contact probability between susceptible and infected individuals and the benefit-to-cost ratio of wearing masks are high. Numerical simulations on random and scale-free networks show that over half of susceptible individuals are prone to wearing masks for self-protection in the early stage of the epidemic outbreak. As a result, voluntarily wearing face masks can effectively slow the spread of the disease and flatten the infection peak. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： complex network Epidemic model Evolutionary game Voluntary mask wearing

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Enhancing Geolocation Accuracy of High-Altitude Airborne SAR Through Tropospheric Delay Compensation

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Xiang, Yaobing Sun, Yuli Lei, Lin Ji, Kefeng Kuang, Gangyao National University of Defense Technology State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology Changsha410073 China

Geolocation is a crucial step in the processing of synthetic aperture radar (SAR) images. High-altitude airborne SAR systems present unique geolocation challenges due to travelling long distances through the troposphere. However, the impact of tropospheric delay on geolocation is often overlooked in existing airborne SAR studies, which can lead to inaccuracies. To address this issue, we propose a new positioning method, the tropospheric delay-compensated range-Doppler (TDC-RD) model. The TDC-RD model leverages reference atmospheric models to estimate and compensate for the tropospheric delay in SAR images. This model effectively mitigates the impact of tropospheric delay in SAR geolocation. To further optimize the TDC-RD model solution, a digital elevation model (DEM)-assisted dual iteration method is proposed. This method iteratively adjusts the target's plane position and elevation in an alternating manner. The effectiveness of the TDC-RD model has been validated through both simulation experiments and actual flight experiments. The results show a significant improvement in geolocation accuracy compared to existing methods, with a maximum reduction of 11.39 m and 24.33% in the mean absolute error (MAE) of SAR geolocation. The TDC-RD model has a great advantage in long-range SAR geolocation. Our research enhances the accuracy and stability of high-altitude airborne SAR geolocation without requiring ground control points. © 2025 IEEE.

关键词： Troposphere

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Micro-macro Wavelet-based Gaussian Splatting for 3D Reconstruction from Unconstrained Images

arXiv

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arXiv 2025年

作者： Li, Yihui Lv, Chengxin Yang, Hongyu Huang, Di State Key Laboratory of Complex and Critical Software Environment Beijing China School of Computer Science and Engineering Beihang University China School of Artificial Intelligence Beihang University China Shanghai Artificial Intelligence Laboratory Shanghai China

3D reconstruction from unconstrained image collections presents substantial challenges due to varying appearances and transient occlusions. In this paper, we introduce Micro-macro Wavelet-based Gaussian Splatting (MW-GS), a novel approach designed to enhance 3D reconstruction by disentangling scene representations into global, refined, and intrinsic components. The proposed method features two key innovations: Micro-macro Projection, which allows Gaussian points to capture details from feature maps across multiple scales with enhanced diversity;and Wavelet-based Sampling, which leverages frequency domain information to refine feature representations and significantly improve the modeling of scene appearances. Additionally, we incorporate a Hierarchical Residual Fusion Network to seamlessly integrate these features. Extensive experiments demonstrate that MW-GS delivers state-of-the-art rendering performance, surpassing existing methods. Copyright © 2025, The Authors. All rights reserved.

关键词： 3D reconstruction

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Adaptive Fuzzy Cooperative Control Based on a Predefined Time Disturbance Observer for MASs

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年

作者： Han, Hong-Gui Hou, Han-Qian Sun, Hao-Yuan Qiao, Jun-Fei The School of Information Science and Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent System The Engineering Research Center of Digital Community Ministry of Education The Beijing Artificial Intelligence Institute The Beijing Laboratory for Intelligent Environmental Protection Beijing University of Technology Beijing100124 China

External disturbances can render constrained multiagent systems (MASs) unstable and affect their convergence speed. To address this issue, the cooperative control strategy for MASs based on a predefined time (PT) disturbance observer (PTDOB) is proposed in this article. First, the original time-varying constrained states of MASs, which are influenced by external disturbances and have a coupled communication topology, are transformed into unconstrained states using the nonlinear transformed function (NTF). This transformation ensures that the limitations of various physical states for agents are not exceeded. Second, the transformed unconstrained states are used to construct the PTDOB for fast observation of external disturbances. Then, based on the proposed PTDOB and the backstepping control technique, an adaptive fuzzy PT cooperative controller is designed. This controller not only ensures the convergence of MASs within PT but also prevents the states from exceeding the time-varying bounds. Finally, the effectiveness of the proposed control strategy is demonstrated through its application to multiple single-link robotic arms as illustrative examples. © 2013 IEEE. All rights reserved.

关键词： Robotic arms

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Fully Distributed Output Regulation of Linear Discrete-Time Multi-Agent systems With Markov Switching Topology

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IEEE Transactions on Circuits and systems I: Regular Papers 2025年 1-9页

作者： Liu, Jiamin Li, Zhao-Yan Zhou, Bin Jimei University School of Science Xiamen361021 China Harbin Institute of Technology School of Mathematics Harbin150001 China Zhengzhou Research Institute of HIT Zhengzhou450000 China Harbin Institute of Technology Center for Control Theory and Guidance Technology Harbin150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150001 China

This paper studies the stochastic cooperative output regulation problem for linear discrete-time multi-agent systems (MASs) with Markov switching topologies and communication/input delays. First, a moment stability criterion for an interconnected time-homogeneous Markov jump linear systems is builded. Then, based on the moment stability criterion, a fully distributed output regulation protocol is designed to solve the stochastic cooperative output regulation problem successively. Finally, a numerical simulation is provided to validate the efficiency of the designed protocol. © 2004-2012 IEEE.

关键词： Topology

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In-situ SR-CT experimental study on rapid densification mechanisms of SiCw/Al composites: Orientation and structural arrangement of whisker

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Composites Part A: Applied science and Manufacturing 2025年 195卷

作者： Wang, Yuanjie Xiao, Yu Li, Yulong Hu, Xiaofang Xu, Feng CAS Key Laboratory of Mechanical Behaviour and Design of Materials Department of Modern Mechanics CAS Center for Excellence in Complex System Mechanics University of Science and Technology of China Anhui Hefei230027 China

For Al matrix composites, SiC whiskers (SiCw), as reinforcement, have a better ability to improve the strength and toughness of the material than particles. However, the current mechanical properties of SiCw/Al composites are still not up to expectations because of more complex factors such as whisker orientation and structure distribution. The key to achieve mechanical property optimization and breakthrough is to understand the relationship among the external field energy, microstructure and sintering process during the preparation of materials. In the present paper, the whole process of SiCw/Al composites microstructure evolution was observed accurately by in situ SR-CT experiment during microwave rapid sintering process. It was revealed that the densification effect of the sample was obviously better than that when the SiC whisker and Al particle neck are perpendicular to each other. It was found that the when the SiC whiskers located in the neck of Al particles were cross-distributed, the matrix density increased more. The angle between the cross-arranged whiskers had a key influence on the densification process of the material. It provided more understanding for the preparation of high performance SiCw/Al composites and raised the possibility for the preparation of more functional materials. © 2025 Elsevier Ltd

关键词： Densification

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Safe RL-based Adaptive Cooperative Game Control of Wing Deformation and Flight State Tracking for Morphing Hypersonic Vehicles

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Wang, Jun-Wei Wang, Feng Wu, Huai-Ning Liu, Zhou-Yang University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Hangzhou International Innovation Institute Hangzhou311115 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

This study addresses the issue of adaptive cooperative game control (ACGC) design for wing deformation and flight state tracking of morphing hypersonic vehicles (MHVs) with variable wing shapes, input constraints and state constraints. To access a better flight control performance, the wing deformation parameter is extended in this work as an auxiliary control input. An oriented-coordinated-control nonlinear differential equation model is first established to describe the complicated longitudinal flight state tracking error dynamics of the MHV. Then, a control barrier function (CBF) is introduced and incorporated into the value function as a risk penalty term of state security constraint. Based on the differential game (DG) theory, the optimal coordinated control problem for the MHV with input constraints and state constraints is treated as a constrained cooperative DG that is further formulated as a Hamilton-Jacobi-Bellman (HJB) equation with barrier and hyperbolic functions. A safe RL algorithm is proposed to solve the above HJB equation and an online Pareto joint control strategy is achieved thereby. Hereafter the stability analysis of the closed-loop state tracking error system is done by the Lyapunov technique. Meanwhile, both state and input constraints are met during the the parameter learning regulation process. At last, a simulation study is performed to support the proposed safe RL-ACGC algorithm. © 2025 IEEE.

关键词： Hyperbolic functions

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Generating Is Believing: Membership Inference Attacks against Retrieval-Augmented Generation

Generating Is Believing: Membership Inference Attacks agains...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yuying Li Gaoyang Liu Chen Wang Yang Yang Key Laboratory of Intelligent Sensing System and Security (Ministry of Education) School of Artificial Intelligence Hubei University Wuhan China Hubei Key Laboratory of Smart Internet Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Retrieval-Augmented Generation (RAG) is a state-of-the-art technique that mitigates issues such as hallucinations and knowledge staleness in Large Language Models (LLMs) by retrieving relevant knowledge from an external database to assist in content generation. Existing research has demonstrated potential privacy risks associated with the LLMs of RAG. However, the privacy risks posed by the integration of an external database, which often contains sensitive data such as medical records or personal identities, have remained largely unexplored. In this paper, we aim to bridge this gap by focusing on membership privacy of RAG’s external database, with the aim of determining whether a given sample is part of the RAG’s database. Our basic idea is that if a sample is in the external database, it will exhibit a high degree of semantic similarity to the text generated by the RAG system. We present S 2 MIA, a Membership Inference Attack that utilizes the Semantic Similarity between a given sample and the content generated by the RAG system. With our proposed S 2 MIA, we demonstrate the potential to breach the membership privacy of the RAG database. Extensive experimental results demonstrate that S 2 MIA outperforms five existing MIAs, even when the system is protected by three representative defenses.

关键词： Data privacy Privacy Databases Large language models Semantics Retrieval augmented generation Focusing Signal processing Solids Speech processing

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