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

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2302.08464
  4. Cited By
Evaluating and Improving the Coreference Capabilities of Machine
  Translation Models

Evaluating and Improving the Coreference Capabilities of Machine Translation Models

Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2023
16 February 2023
Asaf Yehudai
Arie Cattan
Omri Abend
Gabriel Stanovsky
    LRMELM
ArXiv (abs)PDFHTML

Papers citing "Evaluating and Improving the Coreference Capabilities of Machine Translation Models"

2 / 2 papers shown
Title
Maverick: Efficient and Accurate Coreference Resolution Defying Recent
  Trends
Maverick: Efficient and Accurate Coreference Resolution Defying Recent Trends
Giuliano Martinelli
Martin Larsson
Johannes Wiesel
167
21
0
31 Jul 2024
Applying Intrinsic Debiasing on Downstream Tasks: Challenges and
  Considerations for Machine Translation
Applying Intrinsic Debiasing on Downstream Tasks: Challenges and Considerations for Machine Translation
Bar Iluz
Yanai Elazar
Asaf Yehudai
Gabriel Stanovsky
166
4
0
02 Jun 2024
1