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document understanding

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

Papers

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Showing 101–110 of 309 papers

TitleStatusHype
Token-level Correlation-guided Compression for Efficient Multimodal Document UnderstandingCode0
VisFocus: Prompt-Guided Vision Encoders for OCR-Free Dense Document UnderstandingCode1
NAMER: Non-Autoregressive Modeling for Handwritten Mathematical Expression Recognition—0
DANIEL: A fast Document Attention Network for Information Extraction and Labelling of handwritten documentsCode1
Hypergraph based Understanding for Document Semantic Entity RecognitionCode0
A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document UnderstandingCode2
MMLongBench-Doc: Benchmarking Long-context Document Understanding with VisualizationsCode2
ColPali: Efficient Document Retrieval with Vision Language ModelsCode7
DocKylin: A Large Multimodal Model for Visual Document Understanding with Efficient Visual Slimming—0
DrVideo: Document Retrieval Based Long Video Understanding—0
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