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Related papers: End-to-End Document Classification and Key Informa…

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Automating the Key Information Extraction (KIE) from documents improves efficiency, productivity, and security in many industrial scenarios such as rapid indexing and archiving. Many existing supervised learning methods for the KIE task…

Computer Vision and Pattern Recognition · Computer Science 2021-09-30 Minghong Yao , Zhiguang Liu , Liangwei Wang , Houqiang Li , Liansheng Zhuang

Document Key Information Extraction (KIE) is a technology that transforms valuable information in document images into structured data, and it has become an essential function in industrial settings. However, current evaluation metrics of…

Computation and Language · Computer Science 2025-03-27 Minsoo Khang , Sang Chul Jung , Sungrae Park , Teakgyu Hong

Legal practitioners often face a vast amount of documents. Lawyers, for instance, search for appropriate precedents favorable to their clients, while the number of legal precedents is ever-growing. Although legal search engines can assist…

Computation and Language · Computer Science 2022-11-04 Wonseok Hwang , Saehee Eom , Hanuhl Lee , Hai Jin Park , Minjoon Seo

Research in Document Intelligence and especially in Document Key Information Extraction (DocKIE) has been mainly solved as Token Classification problem. Recent breakthroughs in both natural language processing (NLP) and computer vision…

Computation and Language · Computer Science 2023-04-24 Laurent Lam , Pirashanth Ratnamogan , Joël Tang , William Vanhuffel , Fabien Caspani

Computer vision with state-of-the-art deep learning models has achieved huge success in the field of Optical Character Recognition (OCR) including text detection and recognition tasks recently. However, Key Information Extraction (KIE) from…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Wenwen Yu , Ning Lu , Xianbiao Qi , Ping Gong , Rong Xiao

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. Previous approaches…

Artificial Intelligence · Computer Science 2022-06-15 Fengbin Zhu , Chao Wang , Wenqiang Lei , Ziyang Liu , Tat Seng Chua

Information extraction (IE) from documents is an intensive area of research with a large set of industrial applications. Current state-of-the-art methods focus on scanned documents with approaches combining computer vision, natural language…

Computation and Language · Computer Science 2022-08-16 Ismail Oussaid , William Vanhuffel , Pirashanth Ratnamogan , Mhamed Hajaiej , Alexis Mathey , Thomas Gilles

Since real-world ubiquitous documents (e.g., invoices, tickets, resumes and leaflets) contain rich information, automatic document image understanding has become a hot topic. Most existing works decouple the problem into two separate tasks,…

Computer Vision and Pattern Recognition · Computer Science 2021-10-26 Peng Zhang , Yunlu Xu , Zhanzhan Cheng , Shiliang Pu , Jing Lu , Liang Qiao , Yi Niu , Fei Wu

Information extraction from semi-structured documents is crucial for frictionless business-to-business (B2B) communication. While machine learning problems related to Document Information Extraction (IE) have been studied for decades, many…

Information Retrieval · Computer Science 2022-06-23 Matyáš Skalický , Štěpán Šimsa , Michal Uřičář , Milan Šulc

Automating information extraction from form-like documents at scale is a pressing need due to its potential impact on automating business workflows across many industries like financial services, insurance, and healthcare. The key challenge…

Machine Learning · Computer Science 2022-01-14 Beliz Gunel , Navneet Potti , Sandeep Tata , James B. Wendt , Marc Najork , Jing Xie

Table Extraction (TE) consists in extracting tables from PDF documents, in a structured format which can be automatically processed. While numerous TE tools exist, the variety of methods and techniques makes it difficult for users to choose…

Databases · Computer Science 2025-11-21 Marijan Soric , Cécile Gracianne , Ioana Manolescu , Pierre Senellart

Document-level information extraction (IE) tasks have recently begun to be revisited in earnest using the end-to-end neural network techniques that have been successful on their sentence-level IE counterparts. Evaluation of the approaches,…

Computation and Language · Computer Science 2022-09-16 Aliva Das , Xinya Du , Barry Wang , Kejian Shi , Jiayuan Gu , Thomas Porter , Claire Cardie

Unified information extraction (UIE) aims to extract diverse structured information from unstructured text. While large language models (LLMs) have shown promise for UIE, they require significant computational resources and often struggle…

Computation and Language · Computer Science 2025-01-22 Xincheng Liao , Junwen Duan , Yixi Huang , Jianxin Wang

A real-world information extraction (IE) system for semi-structured document images often involves a long pipeline of multiple modules, whose complexity dramatically increases its development and maintenance cost. One can instead consider…

Computation and Language · Computer Science 2021-08-31 Wonseok Hwang , Hyunji Lee , Jinyeong Yim , Geewook Kim , Minjoon Seo

Key Information Extraction (KIE) underpins the understanding of visual documents (e.g., receipts and contracts) by extracting precise semantic content and accurately capturing spatial structure. Yet existing multimodal large language models…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Son Nguyen , Giang Nguyen , Hung Dao , Thao Do , Daeyoung Kim

Advances in the Visually-rich Document Understanding (VrDU) field and particularly the Key-Information Extraction (KIE) task are marked with the emergence of efficient Transformer-based approaches such as the LayoutLM models. Despite the…

Computation and Language · Computer Science 2023-05-01 Seif Laatiri , Pirashanth Ratnamogan , Joel Tang , Laurent Lam , William Vanhuffel , Fabien Caspani

Key information extraction (KIE) from document images requires understanding the contextual and spatial semantics of texts in two-dimensional (2D) space. Many recent studies try to solve the task by developing pre-trained language models…

Computation and Language · Computer Science 2022-04-06 Teakgyu Hong , Donghyun Kim , Mingi Ji , Wonseok Hwang , Daehyun Nam , Sungrae Park

In the rapidly evolving field of scientific research, efficiently extracting key information from the burgeoning volume of scientific papers remains a formidable challenge. This paper introduces an innovative framework designed to automate…

Information Retrieval · Computer Science 2024-01-31 Yangyang Liu , Shoubin Li

Declaration of Performance (DoP) documents, mandated by EU regulation, specify characteristics of construction products, such as fire resistance and insulation. While this information is essential for quality control and reducing carbon…

Computation and Language · Computer Science 2026-01-15 Gaye Colakoglu , Gürkan Solmaz , Jonathan Fürst

Document information extraction tasks performed by humans create data consisting of a PDF or document image input, and extracted string outputs. This end-to-end data is naturally consumed and produced when performing the task because it is…

Computation and Language · Computer Science 2021-04-26 Rasmus Berg Palm , Florian Laws , Ole Winther
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