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GRaSP: Latency-Aware Optimization for Geo-Distributed Retrieval-Augmented Generation
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Researchers introduced GRaSP, a re-scoring algorithm for geo-distributed RAG pipelines balancing latency, egress cost, and accuracy.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 21 October 2026
- Collected by OneBench
- 22 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2610.26938v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is increasingly served across geo-distributed cloud and edge infrastructures, where wide-area latency, cross-region egress cost, and data-residency…
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