SPI: Query-Depth-Adaptive Indexing for Streaming RAG in Vector Databases

arXiv:2511.16681v3 Announce Type: replace Abstract: Vector databases (VecDBs) are increasingly deployed in retrieval-augmented generation (RAG) pipelines where query processing and document ingestion occur concurrently. The index layer needs to provide low-latency search while incorporating new vectors without frequent global rebuilding. Existing VecDB pipelines typically operate within a uniform representation regime, despite substantial variation in the semantic granularity required across queries. This motivates an index design that supports incremental updates while adapting retrieval dept

Source: arXiv cs.CL — read the full report at the original publisher.

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