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Entity-Switched Datasets: An Approach to Auditing the In-Domain
  Robustness of Named Entity Recognition Models
v1v2 (latest)

Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models

8 April 2020
Oshin Agarwal
Yinfei Yang
Byron C. Wallace
A. Nenkova
ArXiv (abs)PDFHTML

Papers citing "Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models"

13 / 13 papers shown
A Multilingual Evaluation of NER Robustness to Adversarial Inputs
A Multilingual Evaluation of NER Robustness to Adversarial InputsWorkshop on Representation Learning for NLP (RepL4NLP), 2023
A. Srinivasan
Sowmya Vajjala
AAML
252
6
0
30 May 2023
Can NLP Models Correctly Reason Over Contexts that Break the Common
  Assumptions?
Can NLP Models Correctly Reason Over Contexts that Break the Common Assumptions?
Neeraj Varshney
Mihir Parmar
Nisarg Patel
Divij Handa
Sayantan Sarkar
Man Luo
Chitta Baral
LRM
217
5
0
20 May 2023
T-NER: An All-Round Python Library for Transformer-based Named Entity
  Recognition
T-NER: An All-Round Python Library for Transformer-based Named Entity RecognitionConference of the European Chapter of the Association for Computational Linguistics (EACL), 2022
Asahi Ushio
Jose Camacho-Collados
256
94
0
09 Sep 2022
What do we Really Know about State of the Art NER?
What do we Really Know about State of the Art NER?International Conference on Language Resources and Evaluation (LREC), 2022
Sowmya Vajjala
Ramya Balasubramaniam
289
21
0
29 Apr 2022
On the Robustness of Reading Comprehension Models to Entity Renaming
On the Robustness of Reading Comprehension Models to Entity Renaming
Jun Yan
Yang Xiao
Sagnik Mukherjee
Bill Yuchen Lin
Robin Jia
Xiang Ren
432
22
0
16 Oct 2021
RockNER: A Simple Method to Create Adversarial Examples for Evaluating
  the Robustness of Named Entity Recognition Models
RockNER: A Simple Method to Create Adversarial Examples for Evaluating the Robustness of Named Entity Recognition Models
Bill Yuchen Lin
Wenyang Gao
Jun Yan
Ryan Rene Moreno
Xiang Ren
AAML
177
50
0
12 Sep 2021
Entity-Based Knowledge Conflicts in Question Answering
Entity-Based Knowledge Conflicts in Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP), 2021
Shayne Longpre
Kartik Perisetla
Anthony Chen
Nikhil Ramesh
Chris DuBois
Sameer Singh
HILM
980
345
0
10 Sep 2021
Context-aware Adversarial Training for Name Regularity Bias in Named
  Entity Recognition
Context-aware Adversarial Training for Name Regularity Bias in Named Entity RecognitionTransactions of the Association for Computational Linguistics (TACL), 2021
Abbas Ghaddar
Philippe Langlais
Ahmad Rashid
Mehdi Rezagholizadeh
312
48
0
24 Jul 2021
Neural Data Augmentation via Example Extrapolation
Neural Data Augmentation via Example Extrapolation
Kenton Lee
Kelvin Guu
Luheng He
Timothy Dozat
Hyung Won Chung
175
75
0
02 Feb 2021
Re-imagining Algorithmic Fairness in India and Beyond
Re-imagining Algorithmic Fairness in India and BeyondConference on Fairness, Accountability and Transparency (FAccT), 2021
Nithya Sambasivan
Erin Arnesen
Ben Hutchinson
Tulsee Doshi
Vinodkumar Prabhakaran
FaML
322
233
0
25 Jan 2021
How Do Your Biomedical Named Entity Recognition Models Generalize to
  Novel Entities?
How Do Your Biomedical Named Entity Recognition Models Generalize to Novel Entities?IEEE Access (IEEE Access), 2021
Hyunjae Kim
Jaewoo Kang
AI4CE
522
27
0
01 Jan 2021
Example-Based Named Entity Recognition
Example-Based Named Entity Recognition
Morteza Ziyadi
Yuting Sun
Abhishek Goswami
Jade Huang
Weizhu Chen
192
35
0
24 Aug 2020
Interpretability Analysis for Named Entity Recognition to Understand
  System Predictions and How They Can Improve
Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can ImproveInternational Conference on Computational Logic (ICCL), 2020
Oshin Agarwal
Yinfei Yang
Byron C. Wallace
A. Nenkova
157
42
0
09 Apr 2020
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