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Xiaolong Xu

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#edge computing Nov 2026

Collaborative Large Model Caching and Inference Offloading With Parameter Sharing in MEC

Pretrained Foundation Models (PFMs) enable highaccuracy inference services but are typically deployed in remote datacenters, resulting in prohibitively high inference delay. Mobile Edge Computing (MEC) can mitigate such high delays by caching PFMs or their fine-tuned variants on cloudlets located close to end users. Ho...

Li-Zhe Zhou, Qiu-Fen Xia, Zi-Chuan Xu et al. · 0 citations
Book Open access Aug 2026

Slow-OCast: Slow-Varying Motion Inspired Transfer Learning for Regional High-Resolution Ocean Environmental Forecasting

This work introduces Slow-OCast, a transfer-learning based model designed for high-resolution ocean environmental forecasting that incorporates the slow-varying motion characteristics of the ocean and comprises two insightful modules.

Qi-Xiu Li, Xiang Zhu, Xiao-Yong Li et al. · 0 citations
Book Open access Jul 2026

Fourier Kolmogorov-Arnold Network and Hypergraph Enhanced Contrastive Learning for Recommendation

Recommendation plays a crucial role in the modern Web ecosystem, powering personalized services across e-commerce, social platforms, and online content networks. To model complex user–item interactions in such Web environments, Graph Neural Networks (GNNs) have become a popular and effective approach due to their abili...

Yuwen Liu, Lianyong Qi, Xucheng Zhou et al. · 0 citations
2026

HD-CLIP: Hierarchical Dynamic Prompting and Decoupled Learning for Zero-Shot Anomaly Detection

The potential of vision-language models (VLMs) such as CLIP for zero-shot anomaly detection (ZSAD) is constrained by an inherent semantic-localization dichotomy. While CLIP’s global features excel at image-level classification, they lack the spatial sensitivity required for pixel-level segmentation. Existing approaches...

Jielin Jiang, Yunxiang Chang, Hao Yin et al. · 0 citations
Book Open access Aug 2026

Slow-OCast: Slow-Varying Motion Inspired Transfer Learning for Regional High-Resolution Ocean Environmental Forecasting

Regional high-resolution ocean environmental forecasting combines spatial numerical modeling with temporal prediction, and is essential for monitoring the ecological security of specific ocean regions. In recent years, deep learning methods are generally more computationally efficient than traditional numerical models...

Qixiu Li, Xiang Zhu, Xiaoyong Li et al. · 0 citations
2026

An Efficient Docking-Point Deployment and Charging Access Coordination Method for Embodied-Enhanced UAV Networks

As embodied intelligent agents, uncrewed aerial vehicles (UAVs) support low-altitude urban services, but their endurance is fundamentally constrained by limited onboard battery capacity. Existing solutions in dense urban environments incur high deployment costs, use coarse spatial layouts, and do not scale to large UAV...

Wei Yang, Jiajie Xu, Jie Chen et al. · 0 citations
#edge computing Sep 2026

MERA: A Green Edge Resource Control System With Privacy-Preservation via Mean-Field Reinforcement Learning

The global rollout of 5G networks has spurred the rapid deployments of edge servers for hosting latency-sensitive web applications, which improves quality of experience (QoE). However, current efforts fall short in the substantial energy costs associated with the 24/7 operation of edge servers and overlook user privacy...

Ziqi Wang, Xiaoyu Xia, Ibrahim Khalil et al. · 0 citations

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