LFRAG: Layout-oriented Fine-grained Retrieval-Augmented Generation on Multimodal Document Understanding
arXiv 2605.22829•cd11a086e2a132cd4afb6a0f05d9585082fd1aeaa0472d689f3df3cb431647f9
AI-Friendly-LaTeXAKT-RecHARNESS-LMLFDocQALaTeX-processingRAG4OutcomeTPMM-DPOblock-level-retrievaldirect-preference-optimizationdistillationdocument-understandingefficiency-latency-optimization','audit'generative-recommenderslayout-segmentationlong-tail-recommendationmedical-AImodel-mergingmodel-scalingmultimodalproduction-MLprognostic-predictionrecommender-systemsretrieval-augmented-generationsemantic-IDssponsored-search
Paper metadata
- arXiv ID
- 2605.22829
- 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
- cd11a086e2a132cd4afb6a0f05d9585082fd1aeaa0472d689f3df3cb431647f9
- Enrichment time
- 2026-05-25T08:52:27Z
- AI-assisted enrichment
- Yes
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