ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2011.04521
  4. Cited By
Automated Discovery of Mathematical Definitions in Text with Deep Neural
  Networks

Automated Discovery of Mathematical Definitions in Text with Deep Neural Networks

9 November 2020
N. Vanetik
Marina Litvak
Sergey Shevchuk
L. Reznik
ArXiv (abs)PDFHTML

Papers citing "Automated Discovery of Mathematical Definitions in Text with Deep Neural Networks"

7 / 7 papers shown
Mathematical Entities: Corpora and Benchmarks
Mathematical Entities: Corpora and Benchmarks
Jacob Collard
Valeria C V de Paiva
Eswaran Subrahmanian
195
1
0
17 Jun 2024
MathGloss: Building mathematical glossaries from text
MathGloss: Building mathematical glossaries from text
Lucy Horowitz
Valeria C V de Paiva
102
4
0
21 Nov 2023
Parmesan: mathematical concept extraction for education
Parmesan: mathematical concept extraction for education
Jacob Collard
Valeria C V de Paiva
Eswaran Subrahmanian
329
3
0
13 Jul 2023
Complex Mathematical Symbol Definition Structures: A Dataset and Model
  for Coordination Resolution in Definition Extraction
Complex Mathematical Symbol Definition Structures: A Dataset and Model for Coordination Resolution in Definition Extraction
Anna Martin-Boyle
Andrew Head
Kyle Lo
Risham Sidhu
Marti A. Hearst
Luan Tuyen Chau
164
1
0
24 May 2023
ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of
  Scientific Concepts
ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of Scientific ConceptsConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Sonia K. Murthy
Kyle Lo
Daniel King
Chandra Bhagavatula
Bailey Kuehl
Sophie Johnson
Jon Borchardt
Daniel S. Weld
Kyle Lo
Doug Downey
200
12
0
14 May 2022
Understanding Jargon: Combining Extraction and Generation for Definition
  Modeling
Understanding Jargon: Combining Extraction and Generation for Definition ModelingConference on Empirical Methods in Natural Language Processing (EMNLP), 2021
Jie Huang
Hanyin Shao
Kevin Chen-Chuan Chang
Jinjun Xiong
Wen-mei W. Hwu
184
20
0
14 Nov 2021
Document-Level Definition Detection in Scholarly Documents: Existing
  Models, Error Analyses, and Future Directions
Document-Level Definition Detection in Scholarly Documents: Existing Models, Error Analyses, and Future Directions
Luan Tuyen Chau
Andrew Head
Risham Sidhu
Kyle Lo
Daniel S. Weld
Marti A. Hearst
278
26
0
11 Oct 2020
1
Page 1 of 1