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Verifying the Robustness of Automatic Credibility Assessment
v1v2 (latest)

Verifying the Robustness of Automatic Credibility Assessment

Natural Language Processing (NLP), 2023
14 March 2023
Piotr Przybyła
A. Shvets
Horacio Saggion
    DeLMOAAML
ArXiv (abs)PDFHTML

Papers citing "Verifying the Robustness of Automatic Credibility Assessment"

4 / 4 papers shown
Title
NumPert: Numerical Perturbations to Probe Language Models for Veracity Prediction
NumPert: Numerical Perturbations to Probe Language Models for Veracity Prediction
Peter Røysland Aarnes
Vinay Setty
AAMLLRM
96
0
0
13 Nov 2025
When Claims Evolve: Evaluating and Enhancing the Robustness of Embedding Models Against Misinformation EditsAnnual Meeting of the Association for Computational Linguistics (ACL), 2025
Jabez Magomere
Emanuele La Malfa
Manuel Tonneau
Ashkan Kazemi
Scott A. Hale
KELM
512
3
0
05 Mar 2025
Attacking Misinformation Detection Using Adversarial Examples Generated by Language Models
Attacking Misinformation Detection Using Adversarial Examples Generated by Language Models
Piotr Przybyła
Euan McGill
Horacio Saggion
AAML
175
2
0
28 Oct 2024
OpenFact at CheckThat! 2024: Combining Multiple Attack Methods for
  Effective Adversarial Text Generation
OpenFact at CheckThat! 2024: Combining Multiple Attack Methods for Effective Adversarial Text GenerationConference and Labs of the Evaluation Forum (CLEF), 2024
Włodzimierz Lewoniewski
P. Stolarski
Milena Stróżyna
Elzbieta Lewanska
Aleksandra Wojewoda
Ewelina Księżniak
Marcin Sawiński
AAML
174
4
0
04 Sep 2024
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