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document understanding

Document understanding involves document classification, layout analysis, information extraction, and DocQA.

Papers

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Showing 231–240 of 309 papers

TitleStatusHype
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding—0
MataDoc: Margin and Text Aware Document Dewarping for Arbitrary Boundary—0
MATATA: Weakly Supervised End-to-End MAthematical Tool-Augmented Reasoning for Tabular Applications—0
MATrIX -- Modality-Aware Transformer for Information eXtraction—0
Memory-Augmented Agent Training for Business Document Understanding—0
Merge and Recognize: A Geometry and 2D Context Aware Graph Model for Named Entity Recognition from Visual Documents—0
M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework—0
MMDocBench: Benchmarking Large Vision-Language Models for Fine-Grained Visual Document Understanding—0
mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding—0
mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding—0
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