M-RAG: Making RAG Faster, Stronger, and More Efficient
arXiv 2603.26667•8919e1f762bfdffdd8ac34af93852b59d5bb2381f1037a4340ad86829dc1ba0a
Cuckoo FilterHR automationLLM-as-judgeLongBenchMedQARAGReCQRabstract-bridge-treeagentic AIchunk-free retrievalconversational query rewritingdatasetsefficiencykey-value decompositionknowledge graphslate-interaction scoringlatencylearning-to-rankmultimodal retrievalquery expansionreciprocal rank fusionrecommendation systemsretrieval-augmented generationstructured retrievalvector search
Paper metadata
- arXiv ID
- 2603.26667
- Version
- Not specified by this published record
- Category
- Computer Science — Information Retrieval (cs.IR)
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Evidence and limitations
- Source ID
- arxiv_cs_ir
- Record identifier
- 8919e1f762bfdffdd8ac34af93852b59d5bb2381f1037a4340ad86829dc1ba0a
- Enrichment time
- 2026-03-31T08:52:19Z
- AI-assisted enrichment
- Yes
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