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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
DocLayLLM: An Efficient Multi-modal Extension of Large Language Models for Text-rich Document UnderstandingCode1
Ocean-OCR: Towards General OCR Application via a Vision-Language ModelCode1
DocFormerv2: Local Features for Document UnderstandingCode1
LEMONADE: A Large Multilingual Expert-Annotated Abstractive Event Dataset for the Real WorldCode1
FRAG: Frame Selection Augmented Generation for Long Video and Long Document UnderstandingCode1
A Discrete Variational Recurrent Topic Model without the Reparametrization TrickCode1
Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural NetworksCode1
DocFormer: End-to-End Transformer for Document UnderstandingCode1
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