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document understanding

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

Papers

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Showing 131–140 of 309 papers

TitleStatusHype
ChuLo: Chunk-Level Key Information Representation for Long Document ProcessingCode0
DocKD: Knowledge Distillation from LLMs for Open-World Document Understanding Models—0
DAViD: Domain Adaptive Visually-Rich Document Understanding with Synthetic Insights—0
Leveraging Long-Context Large Language Models for Multi-Document Understanding and Summarization in Enterprise Applications—0
DocMamba: Efficient Document Pre-training with State Space Model—0
Leveraging Distillation Techniques for Document Understanding: A Case Study with FLAN-T5—0
Information Extraction from Visually Rich Documents Using Directed Weighted Graph Neural NetworkCode0
mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding—0
ViRED: Prediction of Visual Relations in Engineering Drawings—0
The MERIT Dataset: Modelling and Efficiently Rendering Interpretable Transcripts—0
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