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Dynamic Task-Chain Reconfiguration for Cooperative Counter-UAV Defense: A Multi-Agent Large Language Model Framework for Automated Heuristic Design
You are already at the latest version The growing affordability, autonomy, and swarming of small unmanned aerial vehicles (UAVs) turn low-altitude defense from single-shot interception into a multi-node cooperative decision problem, in which the loss of sensing, coordination, or engagement nodes breaks the closed loops linking them. This study formulates their recovery as the dynamic reconfiguration of cooperative counter-UAV task chains.
MV-S2CD: A Modality-Bridged Vision Foundation Model-Based Framework for Unsupervised Optical-SAR Change Detection
Submitted: 28 January 2026 You are already at the latest version Unsupervised change detection (UCD) from heterogeneous bitemporal optical–SAR imagery is challenging due to modality discrepancy, speckle/illumination variations, and the absence of change annotations. We propose MV-S2CD, a vision foundation model (VFM)-based framework that learns a modality-bridged latent space and produces dense change maps in a fully unsupervised manner.
Two-Stage Fine-Tuning of Large Vision-Language Models with Hierarchical Prompting for Few-Shot Object Detection in Remote Sensing Images
Submitted: 21 December 2025 You are already at the latest version Few-shot object detection (FSOD) in high-resolution remote sensing (RS) imagery remains challenging due to scarce annotations, large intra-class variability, and high visual similarity between categories, which together limit the generalization ability of convolutional neural network (CNN)-based detectors. To address this issue, we explore leveraging large vision-language models (LVLMs) for FSOD in RS.
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