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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Pang, Hui Li, Chaozhuo Zhang, Litian Wang, Senzhang Zhang, Xi Key Laboratory of Trustworthy Distributed Computing and Service (MoE) Beijing University of Posts and Telecommunications China School of Cyber Science and Technology Beihang University China School of Computer Science and Engineering Central South University China

ISBN: (纸本)157735897X

Fact verification has become increasingly vital in the internet age, driven by the proliferation of false claims and political misinformation. While traditional methods rely predominantly on text-based evidence, multi-modal evidence introduces richer sources of information, offering valuable insights for claim verification. Existing multi-modal verification models often focus on superficial correlations between claims and evidence, neglecting the complex semantic interactions present in fine-grained multi-modal signals. In this paper, we propose a novel framework for multi-modal fact-checking, named Hypergraph Transformer-based Multimodal Fact-Checking (HGTMFC). Our approach captures high-order relationships between different modalities of evidence and claims by leveraging hypergraphs. HGTMFC models the intricate relationships among evidence across various modalities and enhances information propagation through a transformer-based mechanism embedded within the hypergraph. Moreover, we utilize linegraphs to refine this propagation process, further strengthening the model’s reasoning capabilities. Experiments on benchmark datasets demonstrate that our model significantly outperforms existing approaches in multi-modal fact verification. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Modal analysis

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Asialoglycoprotein receptor 1 promotes SARS-CoV-2 infection of human normal hepatocytes

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Signal Transduction and Targeted Therapy 2024年第3期9卷 1199-1208页

作者： Xinyi Yang Xu Zheng Yuqi Zhu Xiaying Zhao Jun Liu Jiangna Xun Songhua Yuan Jun Chen Hanyu Pan Jinlong Yang Jing Wang Zhimin Liang Xiaoting Shen Yue Liang Qinru Lin Huitong Liang Min Li Fei Peng Daru Lu Jianqing Xu Hongzhou Lu Shibo Jiang Ping Zhao Huanzhang Zhu State Key Laboratory of Genetic Engineering and Engineering Research Center of Gene Technology Ministry of EducationInstitute of GeneticsSchool of Life SciencesYiwu Research InstituteFudan UniversityShanghaiChina Department of Microbiology Faculty of Naval MedicineNaval Medical UniversityShanghai 200433China Scientific Research Center Shanghai Public Health Clinical CenterFudan UniversityShanghaiChina Department of Infectious Diseases and Immunology Shanghai Public Health Clinical CenterFudan UniversityShanghaiChina Changzheng Hospital Naval Medical UniversityShanghaiChina Key Laboratory of Medical Molecular Virology(MOE/NHC/CAMS) Shanghai Institute of Infectious Disease and BiosecuritySchool of Basic Medical SciencesFudan UniversityShanghaiChina Department of Infectious Diseases and Nursing Research Institution National Clinical Research Center for Infectious DiseasesThe Third People’s Hospital of ShenzhenShenzhenGuangdongChina

Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)causes multi-organ damage,which includes hepatic dysfunction,as observed in over 50%of COVID-19 *** I converting enzyme(peptidyl-dipeptidase A)2(ACE2)is the primary receptor for SARS-CoV-2 entry into host cells,and studies have shown the presence of intracellular virus particles in human hepatocytes that express ACE2,but at extremely low ***,we asked if hepatocytes might express receptors other than ACE2 capable of promoting the entry of SARS-CoV-2 into *** address this question,we performed a genome-wide CRISPR-Cas9 activation library screening and found that Asialoglycoprotein receptor 1(ASGR1)promoted SARS-CoV-2 pseudovirus infection of HeLa *** Huh-7 cells,simultaneous knockout of ACE2 and ASGR1 prevented SARS-CoV-2 pseudovirus *** the immortalized THLE-2 hepatocyte cell line and primary hepatic parenchymal cells,both of which barely expressed ACE2,SARSCoV-2 pseudovirus could successfully establish an ***,after treatment with ASGR1 antibody or siRNA targeting ASGR1,the infection rate significantly dropped,suggesting that SARS-CoV-2 pseudovirus infects hepatic parenchymal cells mainly through an ASGR1-dependent *** confirmed that ASGR1 could interact with Spike protein,which depends on receptor binding domain(RBD)and N-terminal domain(NTD).Finally,we also used Immunohistochemistry and electron microscopy to verify that SARS-CoV-2 could infect primary hepatic parenchymal *** inhibiting ASGR1 in primary hepatic parenchymal cells by siRNA,the infection efficiency of the live virus decreased ***,these findings indicate that ASGR1 is a candidate receptor for SARS-CoV-2 that promotes infection of hepatic parenchymal cells.

关键词： ACE2 infection glycoprotein

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Making Adversarial Attack Imperceptible in Frequency Domain: A Watermark-based Framework

Making Adversarial Attack Imperceptible in Frequency Domain:...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Hanxiu Zhang Guitao Cao Xinyue Zhang Jing Xiang Chunwei Wu Shanghai Key Laboratory of Trustworthy Computing MoE Engineering Research Center of SW/HW Co-Design Technology and Application East China Normal University Shanghai China

With the development of multimedia communication technology, the image information stored in electronic devices faces increasing privacy risks and requires processing for protection. However, it is found that adversarial perturbations added to images for semantic information protection may corrupt the frequency domain watermarks added for copyright statement. With such challenges, we propose an Adversarial Frequency domain Watermarking (AFW) framework to protect images from both copyright and semantic content. Specifically, the AFW framework constructs the images as adversarial examples by embedding crafted adversarial watermarks in the frequency domain, followed by an optimization algorithm to improve the visual quality. Notably, AFW can generally integrate with existing watermark and attack methods. Extensive experiments on five network models and the ImageNet dataset demonstrate that the AFW framework can achieve information hiding and adversarial attacking goals under visual quality assurance.

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Asymptotic Estimates for Spectral Estimators of Rotationally Invariant Matrices

Asymptotic Estimates for Spectral Estimators of Rotationally...

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IEEE International Symposium on Information Theory

作者： Zhuohang He Xiaojun Yuan Junjie Ma National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu China Institute of Computational Mathematics and Scientific/Engineering Computing AMSS Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

In this paper, we consider the recovery of low-rank matrices from noisy observations using spectral denoisers, where the singular values are denoised through an identical scalar smoothing function. We explore the asymptotic mean squared error (AMSE) of these denoisers within a framework where the rank of the matrix to be recovered grows linearly with the matrix size. We demonstrate that, under arbitrary i.i.d. noise and some mild regularity assumptions, the AMSE converges in probability to a deterministic function of the noise power. Our results are applicable to commonly used denoisers, including the best-rank-r denoiser, the singular-value soft-threshold denoiser, and the singular-value hard-threshold denoiser. To the best of our knowledge, this is the first study to establish an analytical expression for the asymptotic MSE under arbitrary i.i.d. noise. The derived analytical expression depends solely on the empirical distribution of the singular values of the low-rank matrix and the specific form of the spectral denoiser employed.

关键词： Smoothing methods Limiting Noise Noise reduction Noise measurement Information theory

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Complex generalized Gauss-Radau quadrature rules for Hankel transforms of integer order

arXiv

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arXiv 2024年

作者： Wang, Haiyong Wu, Menghan School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China

Complex Gaussian quadrature rules for oscillatory integral transforms have the advantage that they can achieve optimal asymptotic order. However, their existence for Hankel transform can only be guaranteed when the order of the transform belongs to [0, 1/2]. In this paper we consider the construction of generalized Gauss-Radau quadrature rules for Hankel transform. We show that, if adding certain value and derivative information at the left endpoint, then complex generalized Gauss-Radau quadrature rules for Hankel transform of integer order can be constructed with theoretical guarantees. Orthogonal polynomials that are closely related to such quadrature rules are investigated and their existence for even degrees is proved. Numerical experiments are presented to confirm our *** Codes 65R10, 65D32 © 2024, CC BY-NC-ND.

关键词： Integral equations

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GLCF: A Global-Local Multimodal Coherence Analysis Framework for Talking Face Generation Detection 39

GLCF: A Global-Local Multimodal Coherence Analysis Framework...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Chen, Xiaocan Yin, Qilin Liu, Jiarui Lu, Wei Luo, Xiangyang Zhou, Jiantao School of Computer Science and Engineering MoE Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University Guangzhou 510006 China Alibaba Group Hangzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450002 China State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science Faculty of Science and Technology University of Macau 999078 Macao

ISBN: (纸本)157735897X

Talking face generation (TFG) allows for producing lifelike talking videos of any character using only facial images and accompanying text. Abuse of this technology could pose significant risks to society, creating the urgent need for research into corresponding detection methods. However, research in this field has been hindered by the lack of public datasets. In this paper, we construct the first large-scale multi-scenario talking face dataset (MSTF), which contains 22 audio and video forgery techniques, filling the gap of datasets in this field. The dataset covers 11 generation scenarios and more than 20 semantic scenarios, closer to the practical application scenario of TFG. Besides, we also propose a TFG detection framework, which leverages the analysis of both global and local coherence in the multimodal content of TFG videos. Therefore, a region-focused smoothness detection module (RSFDM) and a discrepancy capture-time frame aggregation module (DCTAM) are introduced to evaluate the global temporal coherence of TFG videos, aggregating multi-grained spatial information. Additionally, a visual-audio fusion module (V-AFM) is designed to evaluate audiovisual coherence within a localized temporal perspective. Comprehensive experiments demonstrate the reasonableness and challenges of our datasets, while also indicating the superiority of our proposed method compared to the state-of-the-art deepfake detection approaches. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Public risks

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Towards Efficient Task Offloading at the Edge Based on Meta-Reinforcement Learning with Hybrid Action Space

Towards Efficient Task Offloading at the Edge Based on Meta-...

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IEEE International Conference on Communications (ICC)

作者： Zhao Yang Yuxiang Deng Ting Wang Haibin Cai MoE Engineering Research Center of Software/Hardware Co-design Technology and Application Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China

As a critical concern of multi-access edge computing (MEC), task offloading has received extensive attention. Although deep reinforcement learning (DRL) has achieved great success in resolving the task offloading problem, most existing DRL-based offloading schemes only consider either continuous action space or discrete action space, which results in the loss of optimality of decisions. Moreover, the generalization ability of the existing schemes is still far from adaptive to dynamic changes in the environment. This leads to offloading strategies having to conduct re-sampling and re-training, which largely impairs the offloading efficiency. To address these issues, we propose a novel efficient MEC task offloading scheme based on parameterized meta-reinforcement learning taking hybrid action space into account. We first formulate this problem as a non-convex multi-objective optimization problem. Then, we design a parameterized meta-reinforcement learning algorithm, named Meta-Hybrid-PPO, with hybrid action space to solve the optimization problem. Comprehensive experimental results show that our Meta-Hybrid-PPO not only performs better than existing state-of-the-art methods in reducing task processing latency and computational energy consumption but also achieves better adaptability.

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Dendritic integration inspired artificial neural networks capture data correlation 24

Dendritic integration inspired artificial neural networks ca...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Chongming Liu Jingyang Ma Songting Li Douglas Zhou School of Mathematical Sciences and Institute of Natural Sciences Shanghai Jiao Tong University Shanghai China School of Mathematical Sciences and Institute of Natural Sciences and Ministry of Education Key Laboratory of Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai China School of Mathematical Sciences and Institute of Natural Sciences and Ministry of Education Key Laboratory of Scientific and Engineering Computing and Shanghai Frontier Science Center of Modern Analysis Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798331314385

Incorporating biological neuronal properties into Artificial Neural Networks (ANNs) to enhance computational capabilities is under active investigation in the field of deep learning. Inspired by recent findings indicating that dendrites adhere to quadratic integration rule for synaptic inputs, this study explores the computational benefits of quadratic neurons. We theoretically demonstrate that quadratic neurons inherently capture correlation within structured data, a feature that grants them superior generalization abilities over traditional neurons. This is substantiated by few-shot learning experiments. Furthermore, we integrate the quadratic rule into Convolutional Neural Networks (CNNs) using a biologically plausible approach, resulting in innovative architectures—Dendritic integration inspired CNNs (Dit-CNNs). Our Dit-CNNs compete favorably with state-of-the-art models across multiple classification benchmarks, e.g., ImageNet-1K, while retaining the simplicity and efficiency of traditional CNNs. All source code are available at https://***/liuchongming1999/Dendritic-integration-inspired-CNN-NeurIPS-2024.

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Memristive feature and mechanism induced by laser-doping in defect-free 2D semiconductor materials

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Journal of Semiconductors 2024年第7期45卷 85-91页

作者： Xiaoshan Du Shu Wang Qiaoxuan Zhang Shengyao Chen Fengyou Yang Zhenzhou Liu Zhengwei Fan Lijun Ma Lei Wang Lena Du Zhongchang Wang Cong Wang Bing Chen Qian Liu College of Electronic and Information Engineering Shandong University of Science and TechnologyQingdao 266590China National Center for Nanoscience and Technology&University of Chinese Academy of Sciences Beijing 100190China Hebei University of Water Resources and Electric Engineering Electrical Automation Department Cangzhou 061001China The MOE Key Laboratory of Weak-Light Nonlinear Photonics and International Sino-Slovenian Join Re-search Center on Liquid Crystal Pho-tonics TEDA Institute of Applied Physics and School of PhysicsNankai UniversityTianjin 300457China College of Mathematics and Physics Shandong Advanced Optoelectronic Materials and Technologies Engineering LaboratoryQingdao Uni-versity of Science and TechnologyQingdao 266061China Department of Physics Capital Normal UniversityBeijing 100048China Department of Advanced Materials and Computing International Iberian Nanotechnology Laboratory(INL)4715-330 BragaPortugal College of Mathematics and Physics Beijing University of Chemical TechnologyBeijing 100029China

Memristors as non-volatile memory devices have gained numerous attentions owing to their advantages in storage,in-memory computing, synaptic applications, etc. In recent years, two-dimensional(2D) materials with moderate defects have been discovered to exist memristive feature. However, it is very difficult to obtain moderate defect degree in 2D materials, and studied on modulation means and mechanism becomes urgent and essential. In this work, we realized memristive feature with a bipolar switching and a configurable on/off ratio in a two-terminal MoS_(2) device(on/off ratio ~100), for the first time, from absent to present using laser-modulation to few-layer defect-free MoS_(2)(about 10 layers), and its retention time in both high resistance state and low resistance state can reach 2×10^(4) s. The mechanism of the laser-induced memristive feature has been cleared by dynamic Monte Carlo simulations and first-principles calculations. Furthermore, we verified the universality of the laser-modulation by investigating other 2D materials of TMDs. Our work will open a route to modulate and optimize the performance of 2D semiconductor memristive devices.

关键词： 2D-material memristor laser doping laser direct writing memristive mechanism

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Magnetoresistance Oscillations in Vertical Junctions of 2D Antiferromagnetic Semiconductor CrPS4

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Physical Review X 2024年第4期14卷 041065-041065页

作者： Pengyuan Shi Xiaoyu Wang Lihao Zhang Wenqin Song Kunlin Yang Shuxi Wang Ruisheng Zhang Liangliang Zhang Takashi Taniguchi MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter Shaanxi Province Key Laboratory of Advanced Materials and Mesoscopic Physics School of Physics Xi’an Jiaotong University Xi’an 710049 China State Key Laboratory of Surface Physics and Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 China State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Xi’an 710049 China Research Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan

Magnetoresistance (MR) oscillations serve as a hallmark of intrinsic quantum behavior, traditionally observed only in conducting systems. Here we report the discovery of MR oscillations in an insulating system, the vertical junctions of CrPS4 which is a two-dimensional A-type antiferromagnetic semiconductor. Systematic investigations of MR peaks under varying conditions, including electrode materials, magnetic field direction, temperature, voltage bias, and layer number, elucidate a correlation between MR oscillations and spin-canted states in CrPS4. Experimental data and analysis point out the important role of the in-gap electronic states in generating MR oscillations, and we propose that spin selected interlayer hopping of localized defect states may be responsible for it. Our findings not only illuminate the unusual electronic transport in CrPS4 but also underscore the potential of van der Waals magnets for exploring interesting phenomena.

关键词： Van der Waals forces

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