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Ruikun Luo

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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

Structure Is All You Need to Reuse: Accelerating GraphRAG via Meta-Structure-Aware KV Caching

MetaKV is proposed, the first structure-aware KV caching mechanism that explicitly decouples static structural logic from dynamic entity semantics in GraphRAG inference, enabling high-throughput, low-latency GraphRAG without sacrificing adherence to graph topology.

Rui-Kun Luo, C. Gu, Jing Yang et al. · 0 citations
Book Open access Aug 2026

Structure Is All You Need to Reuse: Accelerating GraphRAG via Meta-Structure-Aware KV Caching

MetaKV is proposed, the first structure-aware KV caching mechanism that explicitly decouples static structural logic from dynamic entity semantics in GraphRAG inference, enabling high-throughput, low-latency GraphRAG without sacrificing adherence to graph topology.

Ruikun Luo, C. Gu, Jing Yang et al. · 0 citations

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