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document understanding

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

Papers

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Showing 21–30 of 309 papers

TitleStatusHype
Adaptive Markup Language Generation for Contextually-Grounded Visual Document UnderstandingCode1
Automated Parsing of Engineering Drawings for Structured Information Extraction Using a Fine-tuned Document Understanding Transformer—0
FRAG: Frame Selection Augmented Generation for Long Video and Long Document UnderstandingCode1
Evaluating Menu OCR and Translation: A Benchmark for Aligning Human and Automated Evaluations in Large Vision-Language ModelsCode0
Relation-Rich Visual Document Generator for Visual Information ExtractionCode0
NoTeS-Bank: Benchmarking Neural Transcription and Search for Scientific Notes Understanding—0
QID: Efficient Query-Informed ViTs in Data-Scarce Regimes for OCR-free Visual Document Understanding—0
How does Watermarking Affect Visual Language Models in Document Understanding?—0
Improving Applicability of Deep Learning based Token Classification models during Training—0
M-DocSum: Do LVLMs Genuinely Comprehend Interleaved Image-Text in Document Summarization?Code0
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