# American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers arXiv: https://arxiv.org/abs/2308.12477 ยท HTML: https://mlsanity.com/paper/2308.12477/ ## Key facts - Cited by 11 papers in the map (data through 14 Oct 2026). - Builds on 23 of its 34 references that are in the map. - First posted on arXiv 24 Aug 2023. ## Builds on (most cited first, 23 of 23) - [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020) - [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019) - [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019) - [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021) - [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019) - [Segment Anything](https://mlsanity.com/paper/2304.02643/) (2023) - [Representation Learning with Contrastive Predictive Coding](https://mlsanity.com/paper/1807.03748/) (2018) - [Supervised Contrastive Learning](https://mlsanity.com/paper/2004.11362/) (2020) - [Billion-scale similarity search with GPUs](https://mlsanity.com/paper/1702.08734/) (2017) - [Searching for MobileNetV3](https://mlsanity.com/paper/1905.02244/) (2019) - [Datasheets for Datasets](https://mlsanity.com/paper/1803.09010/) (2018) - [Cascade R-CNN: Delving into High Quality Object Detection](https://mlsanity.com/paper/1712.00726/) (2017) - [MPNet: Masked and Permuted Pre-training for Language Understanding](https://mlsanity.com/paper/2004.09297/) (2020) - [Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization](https://mlsanity.com/paper/1603.06560/) (2016) - [From Louvain to Leiden: guaranteeing well-connected communities](https://mlsanity.com/paper/1810.08473/) (2018) - [XCiT: Cross-Covariance Image Transformers](https://mlsanity.com/paper/2106.09681/) (2021) - [Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP](https://mlsanity.com/paper/2212.14024/) (2022) - [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://mlsanity.com/paper/2109.10282/) (2021) - [Revisiting the Sibling Head in Object Detector](https://mlsanity.com/paper/2003.07540/) (2020) - [Noise-Robust De-Duplication at Scale](https://mlsanity.com/paper/2210.04261/) (2022) - [The Newspaper Navigator Dataset: Extracting And Analyzing Visual Content from 16 Million Historic Newspaper Pages in Chronicling America](https://mlsanity.com/paper/2005.01583/) (2020) - [Efficient OCR for Building a Diverse Digital History](https://mlsanity.com/paper/2304.02737/) (2023) - [A Massive Scale Semantic Similarity Dataset of Historical English](https://mlsanity.com/paper/2306.17810/) (2023) ## Built on by (most cited first, 11 of 11) - [The Lucie-7B LLM and the Lucie Training Dataset: Open resources for multilingual language generation](https://mlsanity.com/paper/2503.12294/) (2025) - [CHURRO: Making History Readable with an Open-Weight Large Vision-Language Model for High-Accuracy, Low-Cost Historical Text Recognition](https://mlsanity.com/paper/2509.19768/) (2025) - [EfficientOCR: An Extensible, Open-Source Package for Efficiently Digitizing World Knowledge](https://mlsanity.com/paper/2310.10050/) (2023) - [Large Language Models Meet Computer Vision: A Brief Survey](https://mlsanity.com/paper/2311.16673/) (2023) - [Newswire: A Large-Scale Structured Database of a Century of Historical News](https://mlsanity.com/paper/2406.09490/) (2024) - [Reading the unreadable: Creating a dataset of 19th century English newspapers using image-to-text language models](https://mlsanity.com/paper/2502.14901/) (2025) - [Multimodal LLMs for Historical Dataset Construction from Archival Image Scans: German Patents (1877-1918)](https://mlsanity.com/paper/2512.19675/) (2025) - [A Survey of OCR Evaluation Methods and Metrics and the Invisibility of Historical Documents](https://mlsanity.com/paper/2603.25761/) (2026) - [A Language Model from 1913: Pretraining on Historical Text](https://mlsanity.com/paper/2606.02991/) (2026) - [Southern Newswires: A Large-Scale Study of Mid-Century Wire Content Beyond the Front Page](https://mlsanity.com/paper/2502.11866/) (2025) - [Chronos: The AI Co-Historian](https://mlsanity.com/paper/2604.03553/) (2026) ## Abstract (arXiv) 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. OCR quality can also be low. This study develops a novel, deep learning pipeline for extracting full article texts from newspaper images and applies it to the nearly 20 million scans in Library of Congress's public domain Chronicling America collection. The pipeline includes layout detection, legibility classification, custom OCR, and association of article texts spanning multiple bounding boxes. To achieve high scalability, it is built with efficient architectures designed for mobile phones. The resulting American Stories dataset provides high quality data that could be used for pre-training a large language model to achieve better understanding of historical English and historical world knowledge. The dataset could also be added to the external database of a retrieval-augmented language model to make historical information - ranging from interpretations of political events to minutiae about the lives of people's ancestors - more widely accessible. Furthermore, structured article texts facilitate using transformer-based methods for popular social science applications like topic classification, detection of reproduced content, and news story clustering. Finally, American Stories provides a massive silver quality dataset for innovating multimodal layout analysis models and other multimodal applications.