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arXiv 2025年

作者： Chen, Zhuo Wang, Xinyu Jiang, Yong Zhang, Zhen Geng, Xinyu Xie, Pengjun Huang, Fei Tu, Kewei School of Information Science and Technology ShanghaiTech University China Shanghai Engineering Research Center of Intelligent Vision and Imaging China Institute for Intelligent Computing Alibaba Group China

Despite the advancements made in Visual Large Language Models (VLLMs), like text Large Language Models (LLMs), they have limitations in addressing questions that require real-time information or are knowledge-intensive. Indiscriminately adopting Retrieval Augmented Generation (RAG) techniques is an effective yet expensive way to enable models to answer queries beyond their knowledge scopes. To mitigate the dependence on retrieval and simultaneously maintain, or even improve, the performance benefits provided by retrieval, we propose a method to detect the knowledge boundary of VLLMs, allowing for more efficient use of techniques like RAG. Specifically, we propose a method with two variants that fine-tunes a VLLM on an automatically constructed dataset for boundary identification. Experimental results on various types of Visual Question Answering datasets show that our method successfully depicts a VLLM’s knowledge boundary based on which we are able to reduce indiscriminate retrieval while maintaining or improving the performance. In addition, we show that the knowledge boundary identified by our method for one VLLM can be used as a surrogate boundary for other VLLMs. Code will be released at https://***/Chord-Chen-30/VLLM-KnowledgeBoundary © 2025, CC BY.

关键词： Visual languages

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A New Dual-Population Evolutionary Algorithm Leveraging Objective-Constraint Relationships for Constrained Multi-Objective Optimization

SSRN

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SSRN 2025年

作者： Ye, Jialu Tan, Chaogui Xia, Yizhang Hou, Zhanglu Liu, Yuan Zou, Juan Hunan Engineering Research Center of intelligent System Optimization and Security Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Hunan National Applied Mathematics Center China Xiangtan University China

Population co-evolution strategies are widely used to handle constrained multi-objective optimization problems (CMOPs). However, existing coevolutionary algorithms oversimplify population collaboration and are rigid in evolving the auxiliary population, ignoring the importance of maintaining population diversity, especially for CMOPs with irregular feasible regions. To tackle this issue, we propose a new dual-population evolutionary algorithm, denoted as AACMO, which attempts to mine the relational features between the unconstrained Pareto front (UPF) and the constrained Pareto front (CPF) to better adapt to CMOPs with various constraints. Specifically, the method is categorized into two phases: a learning phase and an evolving phase. First, the main population (MP) aims to quickly learn the relationships between the UPF and the CPF by leveraging the advantages of different operators, namely, genetic algorithm operators and differential evolution operators, during the learning phase. Secondly, two auxiliary strategies are designed to collaborate with the MP during the evolving phase. These strategies are capable of employing a more effective co-evolution method to assist the MP in maintaining diversity, based on the degree of alignment between the learned UPF and CPF at the end of the learning phase. The effectiveness of AACMO is confirmed through comparative analysis with eight state-of-the-art algorithms across four CMOP benchmark suites. © 2025, The Authors. All rights reserved.

关键词： Optimization algorithms

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Non-volatile and multistate terahertz response in semi-floating-gate graphene field-effect transistors

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Optics Express 2025年第11期33卷 22196-22207页

作者： Jingjing Fu Mengjian Xu Miao Cai Yifan Yao Shuo Lei Wen Cai Yating Cai Fei He Shichen Zhang Xunling Zhang Shicong Hou Shun Tang Qingyang Wang Xuguang Guo Yiming Zhu Shanghai Key Lab of Modern Optical Systems Terahertz Technology Innovation Research Institute Engineering Research Center of Optical Instrument and System Ministry of Education University of Shanghai for Science and Technology Shanghai 200093 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai 200092 China ymzhu@***

Two-dimensional (2D) material photodetector based on semi-floating gate (SFG) structure is expected to achieve multiple functions of information sensing, storage, and processing in a single device. Here, we demonstrated a terahertz (THz) detector based on the graphene/h-BN/graphene SFG structure. The device exhibits an excellent memory behavior and a gate-controlled non-volatile and multistate photothermoelectric (PTE) THz response. A theoretical model is established to systematically investigate the memory and PTE response characteristics, and the numerical results are well consistent with the experimental results. Our research provides valuable insights into the complex optoelectronic behavior of 2D material Semi-Floating-Gate Graphene Field-Effect Transistors (SFG-FETs) and paves the way for the realization of multifunctional photodetectors based on SFG-FET structures.

关键词： Electron beam lithography Infrared detectors Optical imaging Optical microscopy Photodetectors Polymethyl methacrylate

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Distributed Generalized Nash Equilibria Learning for Online Stochastic Aggregative Games

arXiv

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arXiv 2025年

作者： Du, Kaixin Meng, Min Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai200092 China Department of Control Science and Engineering College of Electronics and Information Engineering National Key Laboratory of Autonomous Intelligent Unmanned System Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai Research Institute for Intelligent Autonomous Systems Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai China

This paper investigates online stochastic aggregative games subject to local set constraints and time-varying coupled inequality constraints, where each player possesses a time-varying expectation-valued cost function relying on not only its own decision variable but also an aggregation of all the players’ variables. Each player can only access its local individual cost function and constraints, necessitating partial information exchanges with neighboring players through time-varying unbalanced networks. Additionally, local cost functions and constraint functions are not prior knowledge and only revealed gradually. To learn generalized Nash equilibria of such games, a novel distributed online stochastic algorithm is devised based on push-sum and primal-dual strategies. Through rigorous analysis, high probability bounds on the regret and constraint violation are provided by appropriately selecting decreasing stepsizes. Moreover, for a time-invariant stochastic strongly monotone game, it is shown that the generated sequence by the designed algorithm converges to its variational generalized Nash equilibrium (GNE) almost surely, and the time-averaged sequence converges sublinearly with high probability. Finally, the derived theoretical results are illustrated by numerical simulations. Copyright © 2025, The Authors. All rights reserved.

关键词： Nash equilibrium

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Edge-Assisted Flexible Platooning of Connected and Automated Vehicles Under Traffic Anomaly

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IEEE Transactions on Vehicular Technology 2025年

作者： Gao, Fengkun Yang, Bo Chen, Cailian Guan, Xinping Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

The platooning of connected and automated vehicles (CAVs) has the great potential to significantly improve travel experience in terms of safety, comfortableness, and energy efficiency. However, constrained by sensing range and prediction accuracy, the performance of CAV platoon can not be guaranteed in the scenario of mixed traffic consisting of CAVs and human-driven vehicles (HDVs). This is not only due to the uncertainty of HDVs but also related to the occurrence of various traffic anomalies, such as emergency braking and accidents. In this paper, we aim to investigate an efficient control strategy to guarantee the operation of the platoon in mixed traffic, especially in the case of traffic anomalies. To tackle the problem, an edge-assisted platoon control strategy, called E-CACC, is proposed. First, an error-aware flexible tracking policy is designed to adapt to HDV uncertainties and speed prediction errors. Based on the tracking policy, a zone model predictive control (ZMPC) method is then designed to guarantee travel safety and avoid undesired acceleration. Further, a coordination strategy of CAV platoon and roadside unit (RSU) is proposed to prevent the platoon from potential collision in the case of traffic anomalies, where an event-based communication trigger is designed to determine whether and when the platoon establishes communication links with RSU to acquire exogenous sensing data of anomaly segment. Finally, the evaluation results illustrate the effectiveness of the proposed method in improving travel safety and comfortableness. © 1967-2012 IEEE.

关键词： Braking performance

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Transcriptomic modifications across the genome and potential hazards of pulmonary fibrosis caused by metal-organic frameworks

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Science of the Total Environment 2025年 964卷 178504页

作者： Zhang, Yule Yang, Zhijin Chen, Mengya Xue, Zhiwei Chen, Jingwei Zhao, Mantong Li, Yuhao Kang, Shifei Dai, Bo Zheng, Lulu Zhuang, Songlin Zhang, Dawei Engineering Research Center of Optical Instrument and System The Ministry of Education Shanghai Key Laboratory of Modern Optical System Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment University of Shanghai for Science and Technology Shanghai200093 China Department of Physics and Electronic Engineering Heze University Heze274015 China College of Science University of Shanghai for Science and Technology Shanghai200093 China Department of Environmental Science and Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

Metal-Organic Frameworks (MOFs) have shown great promise in environmental protection, owing to their exceptional properties including ultrahigh surface area and porosity, tunable pore size, and easy chemical functionalization. However, emerging evidence from experimental studies indicates that MOFs have side effects on human health due to metal ions doping, resulting in excessive reactive oxygen species (ROS) production, pro-inflammatory responses, and liver fibrosis. In this study, we investigated the impact of MOF-199 on human bronchial epithelial (HBE) cells by using transcriptome sequencing analysis. The results indicated that the stimulation of MOF-199 enhanced ROS generation, upregulated cytoplasmic Ca2+ levels, then activated the Grb2/SOS/Ras/Raf pathway, induced cell apoptosis, and ultimately resulted in lung fibroblasts through TGF-β secretion. The results were validated in vitro and in vivo. Therefore, it is necessary to carefully evaluate the nanosafety of MOF-199 in environment treatments. © 2025

关键词： Lung cancer

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Evolutionary dynamics of behavioral motivations for cooperation

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Nature Communications 2025年第1期16卷 1-12页

作者： Su, Qi Stewart, Alexander J. School of Automation and Intelligent Sensing Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China Luddy School of Informatics Computing and Engineering Indiana University Bloomington Bloomington IN United States

Human decision-making is shaped by underlying motivations, which reflect both subjective well-being and fundamental biological needs. Different needs are often prioritized and traded off against one another. Here we develop a theoretical framework to study the evolution of behavioral motivations, encompassing both philanthropic (cooperating after personal needs are met) and aspirational (cooperating to fulfill personal needs) motivations. Our findings show that when the ratio of benefits to costs for cooperation exceeds a critical threshold, individuals initially driven by aspirational motivations can transition to philanthropic motivations with a low reference point for cooperation, resulting in increased cooperation. Furthermore, the critical threshold depends on the structure of the underlying social network, with network modifications capable of reversing the evolutionary trajectory of motivations. Our results reveal the complex interplay between needs, motivations, social networks, and decision-making, offering insights into how evolution shapes not only cooperative behaviors but also the motivations behind them. © The Author(s) 2025.

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ColorDynamic: Generalizable, Scalable, Real-time, End-to-end Local Planner for Unstructured and Dynamic Environments

arXiv

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arXiv 2025年

作者： Xin, Jinghao Liang, Zhichao Zhang, Zihuan Wang, Peng Li, Ning Department of Automation Shanghai Jiao Tong University Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

Deep Reinforcement Learning (DRL) has demonstrated potential in addressing robotic local planning problems, yet its efficacy remains constrained in highly unstructured and dynamic environments. To address these challenges, this study proposes the ColorDynamic framework. First, an end-to-end DRL formulation is established, which maps raw sensor data directly to control commands, thereby ensuring compatibility with unstructured environments. Under this formulation, a novel network, Transqer, is introduced. The Transqer enables online DRL learning from temporal transitions, substantially enhancing decision-making in dynamic scenarios. To facilitate scalable training of Transqer with diverse data, an efficient simulation platform E-Sparrow, along with a data augmentation technique leveraging symmetric invariance, are developed. Comparative evaluations against state-of-the-art methods, alongside assessments of generalizability, scalability, and real-time performance, were conducted to validate the effectiveness of ColorDynamic. Results indicate that our approach achieves a success rate exceeding 90% while exhibiting real-time capacity (1.2–1.3 ms per planning). Additionally, ablation studies were performed to corroborate the contributions of individual components. Building on this, the OkayPlan-ColorDynamic (OPCD) navigation system is presented, with simulated and real-world experiments demonstrating its superiority and applicability in complex scenarios. The codebase and experimental demonstrations have been open-sourced on our website1 to facilitate reproducibility and further research. Copyright © 2025, The Authors. All rights reserved.

关键词： Decision making

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Securing Mobile Robotic Networks Against Replacement Attack

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IEEE Transactions on Automatic Control 2025年

作者： Li, Yushan He, Jianping Chen, Cailian Guan, Xinping Cai, Lin Shanghai Jiao Tong University Dept. of Automation China Ministry of Education of China The Key Laboratory of System Control and Information Processing China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China University of Victoria Dept. of Electrical and Computer Engineering BC Canada

The security of mobile robotic networks (MRNs) has been an active research topic in recent years. This paper aims to secure the ubiquitous formation control of MRNs against the replacement attack, where an external robot can replace a formation robot by compromising the communication and physically interfering with the victim simultaneously. To counter this advanced attack, the novel idea of this work is to leverage the physical proximity of the formation shape and the interaction topology among robots for defense design. First, from the physical proximity perspective, we propose the convex neighbor polygon (CNP) to capture the geometric characteristic of the formation robots, and design a CNP-based security mechanism for the robots during the replacement attack. Then, from the interaction perspective, we introduce the indirect controllability to characterize the possibility that the attacker leverages the interaction between robots to deactivate the CNP mechanism, and establish the conditions regarding the topology structure and the attack input to counter the replacement. Finally, based on the obtained conditions, we demonstrate how to design the initiatory topology among the formation robots to enhance the defense performance. Comparative simulations verify the effectiveness of the proposed method. © 1963-2012 IEEE.

关键词： Topology

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Online Queue-Aware Service Migration and Resource Allocation in Mobile Edge computing

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IEEE Transactions on Vehicular Technology 2025年

作者： Du, An Jia, Jie Chen, Jian Wang, Xingwei Huang, Ming Northeastern University School of Computer Science and Engineering Engineering Research Center of Security Technology of Complex Network System Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Northeastern University School of Computer Science and Engineering Shenyang110819 China

Mobile edge computing (MEC) integrated with Network Functions Virtualization (NFV) helps run a wide range of services implemented by Virtual Network Functions (VNFs) deployed at MEC networks. This emerging paradigm offers flexible edge resource management for Internet Service Providers (ISPs) and improves service satisfaction of diverse applications. However, a critical challenge lies in processing extremely unpredictable and bursty traffic flow, especially in event-trigger sensing tasks. In this paper, we study queue-aware service migration and resource allocation in an MEC network, where different devices with different arrival patterns request different network services. To this end, we first formulate a novel long-term operation cost minimization problem subject to the stability of multiple queues by adopting a simultaneous migration scheme and determining resource allocation dynamically. To address the problem efficiently, we propose an online control framework to make decisions without any prior system information. We first adopt the Lyapunov optimization technique to decompose the long-term optimization problem into multi-per-slot subproblems. Then, we adopt a decoupled optimization algorithm based on the coordinate descent method and augmented Lagrangian method to solve the offline mixed integer non-linear programming (MINLP) subproblems. Extensive results reveal that the proposed online optimization framework can efficiently balance queue stability and cost consumption. © 1967-2012 IEEE.

关键词： Mobile edge computing

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