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The Impacts of Unanswerable Questions on the Robustness of Machine
  Reading Comprehension Models

The Impacts of Unanswerable Questions on the Robustness of Machine Reading Comprehension Models

31 January 2023
Son Quoc Tran
Phong Nguyen-Thuan Do
Uyen Le
Matt Kretchmar
    ELM
    AAML
ArXivPDFHTML

Papers citing "The Impacts of Unanswerable Questions on the Robustness of Machine Reading Comprehension Models"

3 / 3 papers shown
Title
Measure and Improve Robustness in NLP Models: A Survey
Measure and Improve Robustness in NLP Models: A Survey
Xuezhi Wang
Haohan Wang
Diyi Yang
139
130
0
15 Dec 2021
Generating Natural Language Adversarial Examples
Generating Natural Language Adversarial Examples
M. Alzantot
Yash Sharma
Ahmed Elgohary
Bo-Jhang Ho
Mani B. Srivastava
Kai-Wei Chang
AAML
245
914
0
21 Apr 2018
Adversarial Example Generation with Syntactically Controlled Paraphrase
  Networks
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
Mohit Iyyer
John Wieting
Kevin Gimpel
Luke Zettlemoyer
AAML
GAN
185
711
0
17 Apr 2018
1