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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Dengke Han

Institute of Computing Technology, Chinese Academy of Sciences

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Open access Aug 2026

ESR-HGNN: Eliminating Semantic Redundancy for Efficient Mini-Batch HGNN Inference

This work proposes a redundancy-aware HGNN sampling paradigm that leverages a metapath trie to reuse traversal paths, effectively eliminating redundant memory accesses and introduces a reusability-driven metapath grouping technique that optimally clusters metapaths to maximize reusable traversal paths within hardware channels, enhancing efficiency in scenarios with semantic parallelism.

Dengke Han, Mingyu Yan, Duo Wang et al. · 0 citations
Jul 2026

DraftExpert: Expansion-Aware Self-Speculative Decoding for End-Device MoE Inference

DraftExpert is proposed, an expansion-aware self-speculative decoding framework for expert-offloaded MoE inference that improves decode throughput by 1.45x on average, raises draft acceptance to 84~87%, and achieves 86~88% prefetch hit rates.

Dengke Han · 0 citations

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