SOTAVerified

document understanding

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–60 of 309 papers

TitleStatusHype
Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language ModelsCode1
Document Understanding Dataset and Evaluation (DUDE)Code1
LineFormer: Rethinking Line Chart Data Extraction as Instance SegmentationCode1
CCpdf: Building a High Quality Corpus for Visually Rich Documents from Web Crawl DataCode1
M6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout AnalysisCode1
On Web-based Visual Corpus Construction for Visual Document UnderstandingCode1
ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document UnderstandingCode1
DocQueryNet: Value Retrieval with Arbitrary Queries for Form-like DocumentsCode1
Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural NetworksCode1
End-to-end Document Recognition and Understanding with DessurtCode1
Show:102550
← PrevPage 6 of 31Next →

No leaderboard results yet.