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document understanding

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

Papers

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Showing 51–60 of 309 papers

TitleStatusHype
Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language ModelsCode1
ARB: A Comprehensive Arabic Multimodal Reasoning BenchmarkCode1
Docopilot: Improving Multimodal Models for Document-Level UnderstandingCode1
M6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout AnalysisCode1
DocQueryNet: Value Retrieval with Arbitrary Queries for Form-like DocumentsCode1
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document UnderstandingCode1
Ocean-OCR: Towards General OCR Application via a Vision-Language ModelCode1
DocLayLLM: An Efficient and Effective Multi-modal Extension of Large Language Models for Text-rich Document UnderstandingCode1
A Discrete Variational Recurrent Topic Model without the Reparametrization TrickCode1
DocLayLLM: An Efficient Multi-modal Extension of Large Language Models for Text-rich Document UnderstandingCode1
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