CAMI: Cost-Aware Agent-Guided Multi-Indexing for Semantic Retrieval
RAG ingestion pipelines frequently augment search corpus index with semantic enrichment indices (e.g., synthetic queries or summaries generated from corpus chunks) that are subsequently queried alongside the base index to improve retrieval via better alignment between document representations and user intent. While these supplementary representations substantially improve retrieval quality, they introduce a computational bottleneck: the configuration space of enrichment types and generator models is combinatorial, and the cost of exhaustive index-time evaluation scales linearly with corpus size. We introduce CAMI (Cost-Aware Multi-Indexing), a framework that formalizes multi-index constru...
| Authors | Adnan Qidwai, Anand Eswaran, Sonam Mishra et al. |
|---|---|
| Primary category | cs.IR |
| Published | 14 June 2026 |
| Last updated at source | 14 June 2026 |
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