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document understanding

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

Papers

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Showing 101–125 of 309 papers

TitleStatusHype
Acronym Identification and Disambiguation Shared Tasks for Scientific Document Understanding—0
A Multi-Modal Multilingual Benchmark for Document Image Classification—0
A LayoutLMv3-Based Model for Enhanced Relation Extraction in Visually-Rich Documents—0
DOGE: Towards Versatile Visual Document Grounding and Referring—0
DocXChain: A Powerful Open-Source Toolchain for Document Parsing and Beyond—0
Enumeration of Extractive Oracle Summaries—0
A Token-level Text Image Foundation Model for Document Understanding—0
Handling tree-structured text: parsing directory pages—0
Auto-encodeurs pour la compr\'ehension de documents parl\'es (Auto-encoders for Spoken Document Understanding)—0
A User-Centered Concept Mining System for Query and Document Understanding at Tencent—0
DocVLM: Make Your VLM an Efficient Reader—0
Document Understanding for Healthcare Referrals—0
DAViD: Domain Adaptive Visually-Rich Document Understanding with Synthetic Insights—0
Fast-StrucTexT: An Efficient Hourglass Transformer with Modality-guided Dynamic Token Merge for Document Understanding—0
Decontextualization: Making Sentences Stand-Alone—0
Finding Pragmatic Differences Between Disciplines—0
Read and Think: An Efficient Step-wise Multimodal Language Model for Document Understanding and Reasoning—0
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction—0
FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction—0
Document Layout Analysis with Aesthetic-Guided Image Augmentation—0
Friendly Topic Assistant for Transformer Based Abstractive Summarization—0
From Entity Linking to Question Answering -- Recent Progress on Semantic Grounding Tasks—0
AT-BERT: Adversarial Training BERT for Acronym Identification Winning Solution for SDU@AAAI-21—0
Génération de question à partir d’analyse sémantique pour l’adaptation non supervisée de modèles de compréhension de documents (Question generation from semantic analysis for unsupervised adaptation of document understanding models)—0
Harnessing Webpage UIs for Text-Rich Visual Understanding—0
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