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document understanding

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

Papers

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Showing 31–40 of 309 papers

TitleStatusHype
BiblioPage: A Dataset of Scanned Title Pages for Bibliographic Metadata ExtractionCode0
SFDLA: Source-Free Document Layout AnalysisCode0
A Simple yet Effective Layout Token in Large Language Models for Document Understanding—0
MDocAgent: A Multi-Modal Multi-Agent Framework for Document UnderstandingCode3
Marten: Visual Question Answering with Mask Generation for Multi-modal Document UnderstandingCode0
PP-DocBee: Improving Multimodal Document Understanding Through a Bag of TricksCode0
A Token-level Text Image Foundation Model for Document Understanding—0
Zero-Shot Complex Question-Answering on Long Scientific DocumentsCode0
Shakti-VLMs: Scalable Vision-Language Models for Enterprise AI—0
OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language ModelsCode0
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