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document understanding

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

Papers

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Showing 76–100 of 309 papers

TitleStatusHype
Harnessing Webpage UIs for Text-Rich Visual Understanding—0
DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive PerceptionCode9
ChuLo: Chunk-Level Key Information Representation for Long Document ProcessingCode0
ReLayout: Towards Real-World Document Understanding via Layout-enhanced Pre-training—0
LLMMapReduce: Simplified Long-Sequence Processing using Large Language ModelsCode4
PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse SamplingCode2
DocKD: Knowledge Distillation from LLMs for Open-World Document Understanding Models—0
DAViD: Domain Adaptive Visually-Rich Document Understanding with Synthetic Insights—0
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document UnderstandingCode1
Leveraging Long-Context Large Language Models for Multi-Document Understanding and Summarization in Enterprise Applications—0
Oryx MLLM: On-Demand Spatial-Temporal Understanding at Arbitrary ResolutionCode3
DocMamba: Efficient Document Pre-training with State Space Model—0
Leveraging Distillation Techniques for Document Understanding: A Case Study with FLAN-T5—0
One missing piece in Vision and Language: A Survey on Comics UnderstandingCode2
Information Extraction from Visually Rich Documents Using Directed Weighted Graph Neural NetworkCode0
mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding—0
ViRED: Prediction of Visual Relations in Engineering Drawings—0
The MERIT Dataset: Modelling and Efficiently Rendering Interpretable Transcripts—0
DocLayLLM: An Efficient and Effective Multi-modal Extension of Large Language Models for Text-rich Document UnderstandingCode1
SynthDoc: Bilingual Documents Synthesis for Visual Document Understanding—0
Building and better understanding vision-language models: insights and future directions—0
Arctic-TILT. Business Document Understanding at Sub-Billion Scale—0
Mini-Monkey: Alleviating the Semantic Sawtooth Effect for Lightweight MLLMs via Complementary Image PyramidCode5
Deep Learning based Visually Rich Document Content Understanding: A Survey—0
Deep Learning based Key Information Extraction from Business Documents: Systematic Literature Review—0
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