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

Showing 150 of 74 papers

TitleStatusHype
TextMonkey: An OCR-Free Large Multimodal Model for Understanding DocumentCode5
A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document UnderstandingCode2
LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingCode2
LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document UnderstandingCode2
OCRBench: On the Hidden Mystery of OCR in Large Multimodal ModelsCode2
PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksCode1
Key Information Extraction From Documents: Evaluation And GeneratorCode1
Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural NetworksCode1
GenKIE: Robust Generative Multimodal Document Key Information ExtractionCode1
ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document UnderstandingCode1
KVP10k : A Comprehensive Dataset for Key-Value Pair Extraction in Business DocumentsCode1
LAMBERT: Layout-Aware (Language) Modeling for information extractionCode1
BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from DocumentsCode1
Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path PredictionCode1
Form-NLU: Dataset for the Form Natural Language UnderstandingCode1
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document UnderstandingCode1
DocILE Benchmark for Document Information Localization and ExtractionCode1
Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth EvaluationCode1
PEneo: Unifying Line Extraction, Line Grouping, and Entity Linking for End-to-end Document Pair ExtractionCode1
LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document UnderstandingCode0
AMuRD: Annotated Arabic-English Receipt Dataset for Key Information Extraction and ClassificationCode0
LayoutLMv3: Pre-training for Document AI with Unified Text and Image MaskingCode0
MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and UnderstandingCode0
Multimodal weighted graph representation for information extraction from visually rich documents.Code0
Different Tastes of Entities: Investigating Human Label Variation in Named Entity AnnotationsCode0
OmniParser: A Unified Framework for Text Spotting, Key Information Extraction and Table RecognitionCode0
OmniParser: A Unified Framework for Text Spotting Key Information Extraction and Table RecognitionCode0
OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language ModelsCode0
PaddleOCR 3.0 Technical ReportCode0
PP-StructureV2: A Stronger Document Analysis SystemCode0
GeoLayoutLM: Geometric Pre-training for Visual Information ExtractionCode0
GraphRevisedIE: Multimodal Information Extraction with Graph-Revised NetworkCode0
ICDAR2019 Competition on Scanned Receipt OCR and Information ExtractionCode0
Information Extraction from Visually Rich Documents Using Directed Weighted Graph Neural NetworkCode0
Spatial Dual-Modality Graph Reasoning for Key Information ExtractionCode0
Information Redundancy and Biases in Public Document Information Extraction BenchmarksCode0
Class-Agnostic Region-of-Interest Matching in Document ImagesCode0
DoSA : A System to Accelerate Annotations on Business Documents with Human-in-the-LoopCode0
Automatic Metadata Extraction Incorporating Visual Features from Scanned Electronic Theses and DissertationsCode0
XFormParser: A Simple and Effective Multimodal Multilingual Semi-structured Form ParserCode0
See then Tell: Enhancing Key Information Extraction with Vision Grounding0
A LayoutLMv3-Based Model for Enhanced Relation Extraction in Visually-Rich Documents0
CC-OCR: A Comprehensive and Challenging OCR Benchmark for Evaluating Large Multimodal Models in Literacy0
Construction of a Syntactic Analysis Map for Yi Shui School through Text Mining and Natural Language Processing Research0
Data Efficient Training of a U-Net Based Architecture for Structured Documents Localization0
Deep Learning based Key Information Extraction from Business Documents: Systematic Literature Review0
DONUT-hole: DONUT Sparsification by Harnessing Knowledge and Optimizing Learning Efficiency0
DUBLIN -- Document Understanding By Language-Image Network0
Emergency Communication: OTFS-Based Semantic Transmission with Diffusion Noise Suppression0
End-to-End Document Classification and Key Information Extraction using Assignment Optimization0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RORE (GeoLayoutLM)F198.52Unverified
2GeoLayoutLMF197.97Unverified
3LayoutLMv3 LargeF197.46Unverified
4LayoutMask (large)F197.19Unverified
5LayoutMask (base)F196.99Unverified
6TPP (LayoutMask)F196.92Unverified
7LILTF196.07Unverified
8LayoutLMv2LARGEF196.01Unverified
9LayoutLMv2BASEF194.95Unverified
#ModelMetricClaimedVerifiedStatus
1LayoutLMv2LARGE (Excluding OCR mismatch)F197.81Unverified
2RORE (GeoLayoutLM)F196.97Unverified
3LayoutLMv2LARGEF196.61Unverified
4LayoutLMv2BASEF196.25Unverified
5ChatGPT 3.5 SpatialFormatAccuracy77Unverified
#ModelMetricClaimedVerifiedStatus
1LayoutLMv2LARGEF185.2Unverified
2LayoutLMv2BASEF183.3Unverified
3LAMBERT (75M)F180.42Unverified
#ModelMetricClaimedVerifiedStatus
1DANF1 (%)95.05Unverified