ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2109.12008
  4. Cited By
Separating Retention from Extraction in the Evaluation of End-to-end
  Relation Extraction

Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction

24 September 2021
Bruno Taillé
Vincent Guigue
Geoffrey Scoutheeten
Patrick Gallinari
ArXivPDFHTML

Papers citing "Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction"

4 / 4 papers shown
Title
REXEL: An End-to-end Model for Document-Level Relation Extraction and
  Entity Linking
REXEL: An End-to-end Model for Document-Level Relation Extraction and Entity Linking
N. Bouziani
Shubhi Tyagi
Joseph Fisher
Jens Lehmann
Andrea Pierleoni
SyDa
27
0
0
19 Apr 2024
MedDistant19: Towards an Accurate Benchmark for Broad-Coverage
  Biomedical Relation Extraction
MedDistant19: Towards an Accurate Benchmark for Broad-Coverage Biomedical Relation Extraction
Saadullah Amin
Pasquale Minervini
David Chang
Pontus Stenetorp
G. Neumann
20
3
0
10 Apr 2022
Span-based Joint Entity and Relation Extraction with Transformer
  Pre-training
Span-based Joint Entity and Relation Extraction with Transformer Pre-training
Markus Eberts
A. Ulges
LRM
ViT
164
378
0
17 Sep 2019
Language Models as Knowledge Bases?
Language Models as Knowledge Bases?
Fabio Petroni
Tim Rocktaschel
Patrick Lewis
A. Bakhtin
Yuxiang Wu
Alexander H. Miller
Sebastian Riedel
KELM
AI4MH
406
2,576
0
03 Sep 2019
1