SOTAVerified

Key Information Extraction

Key Information Extraction (KIE) is aimed at extracting structured information (e.g. key-value pairs) from form-style documents (e.g. invoices), which makes an important step towards intelligent document understanding.

Papers

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Showing 1–50 of 74 papers

TitleStatusHype
TextMonkey: An OCR-Free Large Multimodal Model for Understanding DocumentCode5
OCRBench: On the Hidden Mystery of OCR in Large Multimodal ModelsCode2
LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document UnderstandingCode2
LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingCode2
A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document UnderstandingCode2
PEneo: Unifying Line Extraction, Line Grouping, and Entity Linking for End-to-end Document Pair ExtractionCode1
Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural NetworksCode1
ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document UnderstandingCode1
KVP10k : A Comprehensive Dataset for Key-Value Pair Extraction in Business DocumentsCode1
Key Information Extraction From Documents: Evaluation And GeneratorCode1
DocILE Benchmark for Document Information Localization and ExtractionCode1
PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksCode1
Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path PredictionCode1
BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from DocumentsCode1
LAMBERT: Layout-Aware (Language) Modeling for information extractionCode1
Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth EvaluationCode1
Form-NLU: Dataset for the Form Natural Language UnderstandingCode1
GenKIE: Robust Generative Multimodal Document Key Information ExtractionCode1
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document UnderstandingCode1
Entity Relation Extraction as Dependency Parsing in Visually Rich Documents—0
A LayoutLMv3-Based Model for Enhanced Relation Extraction in Visually-Rich Documents—0
CC-OCR: A Comprehensive and Challenging OCR Benchmark for Evaluating Large Multimodal Models in Literacy—0
Construction of a Syntactic Analysis Map for Yi Shui School through Text Mining and Natural Language Processing Research—0
Data Efficient Training of a U-Net Based Architecture for Structured Documents Localization—0
Deep Learning based Key Information Extraction from Business Documents: Systematic Literature Review—0
DONUT-hole: DONUT Sparsification by Harnessing Knowledge and Optimizing Learning Efficiency—0
DUBLIN -- Document Understanding By Language-Image Network—0
Emergency Communication: OTFS-Based Semantic Transmission with Diffusion Noise Suppression—0
End-to-End Document Classification and Key Information Extraction using Assignment Optimization—0
Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models—0
Information Extraction from Documents: Question Answering vs Token Classification in real-world setups—0
Key Information Extraction in Purchase Documents using Deep Learning and Rule-based Corrections—0
KIEval: Evaluation Metric for Document Key Information Extraction—0
Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts—0
LAPDoc: Layout-Aware Prompting for Documents—0
LayoutMask: Enhance Text-Layout Interaction in Multi-modal Pre-training for Document Understanding—0
NCU1415 at ROCLING 2022 Shared Task: A light-weight transformer-based approach for Biomedical Name Entity Recognition—0
One-shot Key Information Extraction from Document with Deep Partial Graph Matching—0
PDFVQA: A New Dataset for Real-World VQA on PDF Documents—0
PPN: Parallel Pointer-based Network for Key Information Extraction with Complex Layouts—0
PrIeD-KIE: Towards Privacy Preserved Document Key Information Extraction—0
RDU: A Region-based Approach to Form-style Document Understanding—0
RealKIE: Five Novel Datasets for Enterprise Key Information Extraction—0
Relational Representation Learning in Visually-Rich Documents—0
Comparison of biomedical relationship extraction methods and models for knowledge graph creation—0
Retrieval Augmented Structured Generation: Business Document Information Extraction As Tool Use—0
See then Tell: Enhancing Key Information Extraction with Vision Grounding—0
SIMARA: a database for key-value information extraction from full pages—0
UniVIE: A Unified Label Space Approach to Visual Information Extraction from Form-like Documents—0
ViBERTgrid: A Jointly Trained Multi-Modal 2D Document Representation for Key Information Extraction from Documents—0
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All datasetsCORDSROIEKleister NDASIMARA

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RORE (GeoLayoutLM)F198.52—Unverified
2GeoLayoutLMF197.97—Unverified
3LayoutLMv3 LargeF197.46—Unverified
4LayoutMask (large)F197.19—Unverified
5LayoutMask (base)F196.99—Unverified
6TPP (LayoutMask)F196.92—Unverified
7LILTF196.07—Unverified
8LayoutLMv2LARGEF196.01—Unverified
9LayoutLMv2BASEF194.95—Unverified
#ModelMetricClaimedVerifiedStatus
1LayoutLMv2LARGE (Excluding OCR mismatch)F197.81—Unverified
2RORE (GeoLayoutLM)F196.97—Unverified
3LayoutLMv2LARGEF196.61—Unverified
4LayoutLMv2BASEF196.25—Unverified
5ChatGPT 3.5 SpatialFormatAccuracy77—Unverified
#ModelMetricClaimedVerifiedStatus
1LayoutLMv2LARGEF185.2—Unverified
2LayoutLMv2BASEF183.3—Unverified
3LAMBERT (75M)F180.42—Unverified
#ModelMetricClaimedVerifiedStatus
1DANF1 (%)95.05—Unverified