7 citations · 10 across the 9 of their papers we have counts for
9 papers
Contrastive Entity Coreference and Disambiguation for Historical Texts
Abhishek Arora, Emily Silcock, Leander Heldring +1
Massive-scale historical document collections are crucial for social science research. Despite increasing digitization, these documents typically lack unique cross-document identif…
Newswire: A Large-Scale Structured Database of a Century of Historical News
Emily Silcock, Abhishek Arora, Luca D'Amico-Wong +1
In the U.S. historically, local newspapers drew their content largely from newswires like the Associated Press. Historians argue that newswires played a pivotal role in creating a…
News Deja Vu: Connecting Past and Present with Semantic Search
Brevin Franklin, Emily Silcock, Abhishek Arora +2
Social scientists and the general public often analyze contemporary events by drawing parallels with the past, a process complicated by the vast, noisy, and unstructured nature of…
EfficientOCR: An Extensible, Open-Source Package for Efficiently Digitizing World Knowledge
Tom Bryan, Jacob Carlson, Abhishek Arora +1
Billions of public domain documents remain trapped in hard copy or lack an accurate digitization. Modern natural language processing methods cannot be used to index, retrieve, and…
LinkTransformer: A Unified Package for Record Linkage with Transformer Language Models
Abhishek Arora, Melissa Dell
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 fo…
American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers
Melissa Dell, Jacob Carlson, Tom Bryan +7
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 fr…
A Massive Scale Semantic Similarity Dataset of Historical English
Emily Silcock, Melissa Dell
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 fr…
Quantifying Character Similarity with Vision Transformers
Xinmei Yang, Abhishek Arora, Shao-Yu Jheng +1
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 us…
Linking Representations with Multimodal Contrastive Learning
Abhishek Arora, Xinmei Yang, Shao-Yu Jheng +1
Many applications require linking individuals, firms, or locations across datasets. Most widely used methods, especially in social science, do not employ deep learning, with record…