SOTAVerified

document understanding

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 81–90 of 309 papers

TitleStatusHype
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
Show:102550
← PrevPage 9 of 31Next →

No leaderboard results yet.