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Semantics Altering Modifications for Evaluating Comprehension in Machine
  Reading
v1v2 (latest)

Semantics Altering Modifications for Evaluating Comprehension in Machine Reading

7 December 2020
Viktor Schlegel
Goran Nenadic
Riza Batista-Navarro
ArXiv (abs)PDFHTML

Papers citing "Semantics Altering Modifications for Evaluating Comprehension in Machine Reading"

12 / 12 papers shown
Pay Attention to Real World Perturbations! Natural Robustness Evaluation in Machine Reading Comprehension
Pay Attention to Real World Perturbations! Natural Robustness Evaluation in Machine Reading Comprehension
Yulong Wu
Viktor Schlegel
Riza Batista-Navarro
AAML
478
2
0
23 Feb 2025
Seemingly Plausible Distractors in Multi-Hop Reasoning: Are Large
  Language Models Attentive Readers?
Seemingly Plausible Distractors in Multi-Hop Reasoning: Are Large Language Models Attentive Readers?Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Neeladri Bhuiya
Viktor Schlegel
Stefan Winkler
LRM
300
10
0
08 Sep 2024
Investigating a Benchmark for Training-set free Evaluation of Linguistic
  Capabilities in Machine Reading Comprehension
Investigating a Benchmark for Training-set free Evaluation of Linguistic Capabilities in Machine Reading Comprehension
Viktor Schlegel
Goran Nenadic
Riza Batista-Navarro
ELM
270
0
0
09 Aug 2024
Desiderata for the Context Use of Question Answering Systems
Desiderata for the Context Use of Question Answering Systems
Sagi Shaier
Lawrence E Hunter
Katharina von der Wense
383
6
0
31 Jan 2024
Guiding LLM to Fool Itself: Automatically Manipulating Machine Reading
  Comprehension Shortcut Triggers
Guiding LLM to Fool Itself: Automatically Manipulating Machine Reading Comprehension Shortcut TriggersConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Mosh Levy
Haiqin Yang
Yoav Goldberg
312
11
0
24 Oct 2023
Gradient-Based Word Substitution for Obstinate Adversarial Examples
  Generation in Language Models
Gradient-Based Word Substitution for Obstinate Adversarial Examples Generation in Language Models
Yimu Wang
Peng Shi
Hongyang Zhang
SILM
220
4
0
24 Jul 2023
Chain-of-Questions Training with Latent Answers for Robust Multistep
  Question Answering
Chain-of-Questions Training with Latent Answers for Robust Multistep Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Peng Guo
Jesse Thomason
Robin Jia
BDLLRM
320
13
0
24 May 2023
A Comprehensive Survey of Sentence Representations: From the BERT Epoch
  to the ChatGPT Era and Beyond
A Comprehensive Survey of Sentence Representations: From the BERT Epoch to the ChatGPT Era and BeyondConference of the European Chapter of the Association for Computational Linguistics (EACL), 2023
Abhinav Ramesh Kashyap
Thang-Tung Nguyen
Viktor Schlegel
Stefan Winkler
See-Kiong Ng
Soujanya Poria
AI4TS3DVSSL
239
17
0
22 May 2023
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine
  Reading Comprehension
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension
Xanh Ho
Johannes Mario Meissner
Saku Sugawara
Akiko Aizawa
OffRL
280
6
0
05 Sep 2022
Robustness Analysis of Video-Language Models Against Visual and Language
  Perturbations
Robustness Analysis of Video-Language Models Against Visual and Language PerturbationsNeural Information Processing Systems (NeurIPS), 2022
Madeline Chantry Schiappa
Shruti Vyas
Hamid Palangi
Yogesh S Rawat
Vibhav Vineet
VLM
643
32
0
05 Jul 2022
Measure and Improve Robustness in NLP Models: A Survey
Measure and Improve Robustness in NLP Models: A Survey
Xuezhi Wang
Haohan Wang
Diyi Yang
638
163
0
15 Dec 2021
Numerical reasoning in machine reading comprehension tasks: are we there
  yet?
Numerical reasoning in machine reading comprehension tasks: are we there yet?
Hadeel Al-Negheimish
Pranava Madhyastha
A. Russo
AIMatReLM
191
15
0
16 Sep 2021
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