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OLALA: Object-Level Active Learning Based Layout Annotation

Journal Article

Layout detection is an essential step for accurately extracting structured contents from historical documents. The intricate and varied layouts present in these document images make it expensive to label the numerous layout regions that can be densely...

LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

Journal Article

Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks. Ideally, research outcomes could be easily deployed in production and extended for further investigation. However, various factors like...

Noise-Robust De-Duplication at Scale

Journal Article

Identifying near duplicates within large, noisy text corpora has a myriad of applications that range from de-duplicating training datasets, reducing privacy risk, and evaluating test set leakage, to identifying reproduced news articles and literature...

Efficient OCR for Building a Diverse Digital History

Working Paper

Thousands of users consult digital archives daily, but the information they can access is unrepresentative of the diversity of documentary history. The sequence-to-sequence architecture typically used for optical character recognition (OCR) – which...

Linking Representations with Multimodal Contrastive Learning

Working Paper

Many applications require grouping instances contained in diverse document datasets into classes. Most widely used methods do not employ deep learning and do not exploit the inherently multimodal nature of documents. Notably, record linkage is typically...

Quantifying Character Similarity with Vision Transformers

Working Paper

Record linkage is a bedrock of quantitative social science, as analyses often require linking data from multiple, noisy sources. Off-the-shelf string matching methods are widely used, as they are straightforward and cheap to implement and scale. Not all...

A Massive Scale Semantic Similarity Dataset of Historical English

Working Paper

 A diversity of tasks use language models trained on semantic similarity data. While there are a variety of datasets that capture semantic similarity, they are either constructed from modern web data or are relatively small datasets created in the past...

American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers

Working Paper

Existing full text datasets of U.S. public domain newspapers do not recognize the often complex layouts of newspaper scans, and as a result the digitized content scrambles texts from articles, headlines, captions, advertisements, and other layout regions...

LinkTransformer: A Unified Package for Record Linkage with Transformer Language Models

Working Paper

Linking information across sources is fundamental to a variety of analyses in social science, business, and government. While large language models (LLMs) offer enormous promise for improving record linkage in noisy datasets, in many domains approximate...

Trafficking Networks and the Mexican Drug War

Journal Article

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GIS For Applied Economists (Lecture Notes Only)

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