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Melissa Dell

15 papers hereh-index 8338 citations18 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2
  • last author11

Across the 14 of 15 papers where every author was matched, so the position is known.

fields
  • cs.CL8
  • cs.CV5
  • cs.LG1
  • econ.EM1
same name
  • Melissa Dell — 3 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202025
most citedLayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

16 citations · 32 across the 15 of their papers we have counts for

collaborators
Showing 2023 · cs.CLShow all

4 papers · 2 filters

cs.CL2023★ 1 cited

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…

cs.CL2023★ 7 cited

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…

cs.CL2023★ 1 cited

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…

cs.CL2023

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.