This paper proposes Lever, a locality-aware collaborative retrieval framework that exploits query locality to accelerate graph-based RAG retrieval, and identifies and empirically validate a previously underexplored property of RAG workloads: strong per-user query locality.
Yong-Heng Deng, Tianyuan Jiang, Zhen-Ya Ma et al.· Proceedings of the 32nd ACM...· 0 citations
Vision-language models (VLMs) have achieved remarkable success, yet their substantial resource demands far exceed the capabilities of typical IoT devices. This paper investigates collaborative VLM inference across IoT devices, mobile UAV relays, and a ground base station to bring intelligence to the edge. The collabora...
Jie Zhao, Shucheng Li, Ming-Liu Liu et al.· 2026 IEEE/CIC International...· 0 citations
Retrieval-Augmented Generation (RAG) grounds large language models in external knowledge and has become a key technique for knowledge-intensive tasks. As knowledge bases continue to scale, however, the retrieval stage increasingly dominates end-to-end latency, limiting the responsiveness of RAG systems. In this paper,...
Yongheng Deng, Tianyuan Jiang, Zhenya Ma et al.· Proceedings of the 32nd ACM...· 0 citations
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