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Wireless Large AI Model: Shaping the AI-Native Future of 6G and Beyond

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arXiv 2025年

作者： Zhu, Fenghao Wang, Xinquan Li, Xinyi Zhang, Maojun Chen, Yixuan Huang, Chongwen Yang, Zhaohui Chen, Xiaoming Zhang, Zhaoyang Jin, Richeng Huang, Yongming Feng, Wei Yang, Tingting Bai, Baoming Gao, Feifei Yang, Kun Liu, Yuanwen Muhaidat, Sami Yuen, Chau Huang, Kaibin Wong, Kai-Kit Niyato, Dusit Debbah, Mérouane College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China School of Automation Southeast University Nanjing210096 China Tsinghua University Beijing100084 China Pengcheng Laboratory Shenzhen518066 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China State Key Laboratory of Novel Software Technology Nanjing University Nanjing210008 China Suzhou215163 China The University of Hong Kong Hong Kong KU 6G Research Center Computer and Communication Engineering Khalifa University Abu Dhabi127788 United Arab Emirates School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi127788 United Arab Emirates

The emergence of sixth-generation and beyond communication systems is expected to fundamentally transform digital experiences through introducing unparalleled levels of intelligence, efficiency, and connectivity. A promising technology poised to enable this revolutionary vision is the wireless large AI model (WLAM), characterized by its exceptional capabilities in data processing, inference, and decision-making. In light of these remarkable capabilities, this paper provides a comprehensive survey of WLAM, elucidating its fundamental principles, diverse applications, critical challenges, and future research opportunities. We begin by introducing the background of WLAM and analyzing the key synergies with wireless networks, emphasizing the mutual benefits. Subsequently, we explore the foundational characteristics of WLAM, delving into their unique relevance in wireless environments. Then, the role of WLAM in optimizing wireless communication systems across various use cases and the reciprocal benefits are systematically investigated. Furthermore, we discuss the integration of WLAM with emerging technologies, highlighting their potential to enable transformative capabilities and breakthroughs in wireless communication. Finally, we thoroughly examine the high-level challenges hindering the practical implementation of WLAM and discuss pivotal future research directions. Copyright © 2025, The Authors. All rights reserved.

关键词： Sorting

software trustworthiness evaluation using structural equation modeling

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International Journal of Performability Engineering 2019年第10期15卷 2628-2635页

作者： Deng, Rumei Chen, Yixiang Wu, Hengyang Tao, Hongwei MoE Engineering Center for Software Hardware Co-Design Technology and Application East China Normal University Shanghai200062 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou450002 China

software trustworthiness evaluation results can provide guidance for existing software development. Therefore, it is of great significance to study software trustworthiness evaluation. Weights and the relationship of trustworthy attributes have a huge effect on the results of software trustworthiness evaluation. However, few studies have considered weights and the quantitative relationship among trustworthy attributes at the same time. Structural equation modeling (SEM) provides a more scientific and reasonable method to obtain weights, where the objectification of subjective weights is guaranteed. In this paper, we propose a SEM-based method to evaluate software trustworthiness. Firstly, we establish the trustworthy evaluation indicator system for software. Based on the survey data, we construct the SEM for software trustworthiness evaluation to obtain the weights of trustworthy attributes and the relationship among them. Lastly, we apply the trustworthy measurement model to calculate the trustworthiness value of software to be surveyed. These trustworthiness values demonstrate the reasonability of our method. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Surveys

Matrix Classifier On Dynamic Functional Connectivity For Mci Identification

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Matrix Classifier On Dynamic Functional Connectivity For Mci...

IEEE International Conference on Image Processing

作者： Lei Zhou Liang Zhang Xiao Bai Jun Zhou School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing State Key Laboratory of Software Development Environment Beihang University Beijing School of Information and Communication Technology Griffith University Nathan

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

One of the most popular method for Alzheimer's disease (AD) diagnosis is exploring the Brain functional connectivity (FC) from resting-state functional magnetic resonance imaging (RS-fMRI). To early prevent AD, it is crucial to distinguish AD and and its preclinical stage, mild cognitive impairment (MCI) and early MCI (eMCI). In many existing works, dynamic functional connectivity (dFC) which contains rich spatiotemporal information has been exploited for the MCI and eMCI identification. However, most of these dFC based methods only consider the correlation between discrete brain status while ignore the valuable spatiotemporal information contained in dFC. To overcome this limitation, we propose a matrix classifier based method on the dFC signal for MCI and eMCI identification. Specifically, we first represent the dFC correlations by matrix features which contain rich spatiotemporal information and then learn the support matrix machines (SMM) to classify AD and its preclinical stage. Experiments on 600 real people data provide by the Alzheimer's Disease Neuroimaging Initiative (ADNI) demonstrate that our proposed matrix classifier based method outperforms other FC and dFC based methods for both normal controls (NC)/MCI identification and NC/eMCI identification.

关键词： Feature extraction Correlation Dementia Microsoft Windows Spatiotemporal phenomena Training

Exploring the Role of Large Language Models in Cybersecurity: A Systematic Survey

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arXiv 2025年

作者： Tian, Shuang Zhang, Tao Liu, Jiqiang Wang, Jiacheng Wu, Xuangou Zhu, Xiaoqiang Zhang, Ruichen Zhang, Weiting Yuan, Zhenhui Mao, Shiwen Kim, Dong In School of Software Engineering Beijing Jiaotong University Beijing100044 China School of Cyberspace Science and Technology Beijing Jiaotong University Beijing100044 China School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore School of Computer Science and Technology An hui Province Key Laboratory of Digital Twin Technology in Metallurgical Industry Anhui University of Technology Anhui243002 China College of Computing and Data Science Nanyang Technological University Singapore School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China School of Engineering University of Warwick CoventryCV4 7AL United Kingdom Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States Department of Electrical and Computer Engineering College of Information and Communication Engineering Sungkyunkwan University Suwon16419 Korea Republic of

—With the rapid development of technology and the acceleration of digitalisation, the frequency and complexity of cyber security threats are increasing. Traditional cybersecurity approaches, often based on static rules and predefined scenarios, are struggling to adapt to the rapidly evolving nature of modern cyberattacks. There is an urgent need for more adaptive and intelligent defence strategies. The emergence of Large Language Model (LLM) provides an innovative solution to cope with the increasingly severe cyber threats, and its potential in analysing complex attack patterns, predicting threats and assisting real-time response has attracted a lot of attention in the field of cybersecurity, and exploring how to effectively use LLM to defend against cyberattacks has become a hot topic in the current research field. This survey examines the applications of LLM from the perspective of the cyber attack lifecycle, focusing on the three phases of defense reconnaissance, foothold establishment, and lateral movement, and it analyzes the potential of LLMs in Cyber Threat Intelligence (CTI) tasks. Meanwhile, we investigate how LLM-based security solutions are deployed and applied in different network scenarios. It also summarizes the internal and external risk issues faced by LLM during its application. Finally, this survey also points out the facing risk issues and possible future research directions in this domain. Copyright © 2025, The Authors. All rights reserved.

关键词： Cyber attacks

Community-based 3-SAT formulas with a predefined solution

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arXiv 2019年

作者： Hu, Yamin Luo, Wenjian Wang, Junteng Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China China

It is crucial to generate crafted SAT formulas with predefined solutions for the testing and development of SAT solvers since many SAT formulas from real-world applications have solutions. Although some generating algorithms have been proposed to generate SAT formulas with predefined solutions, community structures of SAT formulas are not considered in these algorithms. Consequently, we propose a 3-SAT formula generating algorithm that not only guarantees the existence of a predefined solution, but also simultaneously considers community structures and clause distributions. The proposed 3-SAT formula generating algorithm controls the quality of community structures through controlling (1) the number of clauses whose variables have a common community, which we call intra-community clauses, and (2) the number of variables that only belong to one community, which we call intra-community variables. For a SAT formula, more intra-community clauses and intracommunity variables, higher quality of community structures. To study the combined effect of community structures and clause distributions on the hardness of SAT formulas, we measure solving runtimes of two solvers, gluHack (a leading CDCL solver) and CPSparrow (a leading SLS solver), on the generated SAT formulas under different groups of parameter settings. Through extensive experiments, we obtain some noteworthy observations on the SAT formulas generated by the proposed algorithm: (1) The community structure has little or no effects on the hardness of SAT formulas with regard to CPSparrow but a strong effect with regard to gluHack. (2) Only when the proportion of true literals in a SAT formula in terms of the predefined solution is 0.5, SAT formulas are hard-to-solve with regard to gluHack;when this proportion is below 0.5, SAT formulas are hard-to-solve with regard to CPSparrow. (3) When the ratio of the number of clauses to that of variables is around 4.25, the SAT formulas are hard-to-solve with regard to both glu

关键词： Hardness

Many-Modal Optimization by Difficulty-Based Cooperative Co-evolution

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Many-Modal Optimization by Difficulty-Based Cooperative Co-e...

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Wenjian Luo Yingying Qiao Xin Lin Peilan Xu Mike Preuss Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

Evolutionary multimodal optimization has received considerable attention in the past decade. Most existing evolutionary multimodal optimization algorithms are designed to solve problems with relatively few global optima. However, in real-world applications, the problems can possess a lot of global optima (and sometimes acceptable local optima). Finding more global optima can help us learn more about their landscapes and distributions. However, solving these problems with limited computational resources is a challenge for current algorithms. In this paper, many-modal optimization problems are studied, and each of them has more than 100 global optima. We first present a benchmark with 10 many-modal problems based on the existing multimodal optimization benchmarks. The numbers of global optima of these 10 problems vary from 108 to 7776. Second, we propose the difficulty-based cooperative co-evolution (DBCC) strategy for solving many-modal optimization problems. DBCC comprises four primary steps: problem separation, resource allocation, optimization, and solution reconstruction. The clonal selection algorithm is selected as the optimizer in DBCC. Experimental results demonstrate that DBCC provides satisfactory performance.

关键词： Optimization Benchmark testing Sociology Statistics Heuristic algorithms Resource management Search problems

Random directional attack for fooling deep neural networks

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arXiv 2019年

作者： Luo, Wenjian Wu, Chenwang Zhou, Nan Ni, Li Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei Anhui230027 China

Deep neural networks (DNNs) have been widely used in many fields such as images processing, speech recognition;however, they are vulnerable to adversarial examples, and this is a security issue worthy of attention. Because the training process of DNNs converge the loss by updating the weights along the gradient descent direction, many gradient-based methods attempt to destroy the DNN model by adding perturbations in the gradient direction. Unfortunately, as the model is nonlinear in most cases, the addition of perturbations in the gradient direction does not necessarily increase loss. Thus, we propose a random directed attack (RDA) for generating adversarial examples in this paper. Rather than limiting the gradient direction to generate an attack, RDA searches the attack direction based on hill climbing and uses multiple strategies to avoid local optima that cause attack failure. Compared with state-of-the-art gradient-based methods, the attack performance of RDA is very competitive. Moreover, RDA can attack without any internal knowledge of the model, and its performance under black-box attack is similar to that of the white-box attack in most cases, which is difficult to achieve using existing gradient-based attack methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

Empirical Study of Population-Based Dynamic Constrained Multimodal Optimization Algorithms

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Empirical Study of Population-Based Dynamic Constrained Mult...

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Xin Lin Wenjian Luo Yingying Qiao Peilan Xu Tao Zhu Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei China School of Software Engineering University of South China Hengyang China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

There are many dynamic optimization problems in real-world applications. Although many variants of evolutionary algorithms and swarm intelligence have been proposed to solve such problems, little work has been conducted to address the dynamic constrained multimodal optimization problems (DCMMOPs). In DCMMOPs, there exist multiple optimal solutions corresponding to each environment that the algorithm is required to find. Sometimes, it is also necessary to identify the accepted local optima. Therefore, for each environment, the decision maker can select one from among multiple returned solutions according to his/her domain knowledge and/or preferences. The objective of this paper is to test the performance of various combinations of several population-based dynamic multimodal optimization algorithms and popular constraint handling techniques. First, the typical dynamic constrained optimization problems are slightly modified to be in the form of the dynamic constrained multimodal optimization problems. Second, four different population-based dynamic multimodal optimization algorithms, and five different constraint handling techniques, are pairwise tested in the experiments. Experimental results demonstrate that, among the candidates, DCMM-CSA-SR performs most successfully at all accuracy levels.

关键词： Heuristic algorithms Optimization Vehicle dynamics Sociology Statistics Evolutionary computation Clustering algorithms

The Quantum Internet (Technical Version)

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arXiv 2025年

作者： Rohde, Peter P. Huang, Zixin Ouyang, Yingkai Huang, He-Liang Su, Zu-En Devitt, Simon Ramakrishnan, Rohit Mantri, Atul Tan, Si-Hui Liu, Nana Harrison, Scott Radhakrishnan, Chandrashekar Brennen, Gavin K. Baragiola, Ben Q. Dowling, Jonathan P. Byrnes, Tim Munro, William J. Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW Australia Hearne Institute for Theoretical Physics Louisiana State University Baton Rouge United States School of Mathematical and Physical Sciences Macquarie University NSW2109 Australia School of Mathematical and Physical Sciences University of Sheffield SheffieldS3 7RH United Kingdom Henan Key Laboratory of Quantum Information and Cryptography Henan Zhengzhou450000 China Hefei National Laboratory for Physical Sciences at Microscale Department of Modern Physics University of Science & Technology of China Hefei China CAS Centre for Excellence and Synergetic Innovation Centre in Quantum Information & Quantum Physics University of Science & Technology of China Hefei China CAS-Alibaba Quantum Computing Laboratory Shanghai China InstituteQ Aalto University Espoo02150 Finland Indian Institute of Science Bangalore India Singapore University of Technology & Design Singapore Centre for Quantum Technologies National University of Singapore Singapore Horizon Quantum Ireland 24 Fitzwilliam Place Dublin 2 D02 T296 Ireland Institute of Natural Sciences Shanghai Jiao Tong University Shanghai200240 China School of Mathematical Sciences Shanghai Jiao Tong University Shanghai200240 China Ministry of Education Key Laboratory in Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai200240 China Shanghai Artificial Intelligence Laboratory Shanghai China University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai200240 China Leibniz Institute for Research & Information in Education Frankfurt am Main Germany Department of Computer Science and Engineering NYU Shanghai 567 West Yangsi Road Shanghai200124 China Centre of Excellence in Engineered Quantum Systems Macquarie University NSW Australia Centre for Quantum Computation and Communication Technology School of Science RMIT University VIC

The desire to share and unite remote digital assets motivated the development of the classical internet, the enabler of the entire 21st century economy and our modern way of life. As we enter the quantum era, it is to be expected there will be a similar demand for networking quantum assets, motivating a global quantum internet for bringing together the world's quantum resources, leveraging off their exponential trajectory in capability. We present models for quantum networking, how they might be applied in the future, and the implications they will have. Socially, economically, politically and geostrategically, the upcoming era of quantum supremacy will be as significant for the 21st century as the transistor was for the 20th. The inherently different scaling in the computational power of quantum computers fundamentally changes the dynamics of how they will operate in the future. Given their high expected initial cost, a client/server model for outsourcing computation will be essential for enabling the accessibility and proliferation of this technology, and ensuring its economic viability. We therefore anticipate the emergence of cloud quantum computing, a model for outsourcing quantum computations to the network. We argue that economic efficiency will mandate that all future quantum computers be united into a single global virtual quantum computer, offering exponentially more power to all network participants than if they were to keep their resources to themselves. This model for the allocation of computational resources is uniquely quantum, with no classical analogue, completely altering the economic landscape for the future of computation. Given the sensitivity of much of the data to which future quantum computers are going to foreseeably be applied, protocols for encrypted quantum computation will be essential - the outsourcing of computations that neither an eavesdropper nor even the server performing the computation can spy upon. This will enable new models fo

关键词： Outsourcing