Verifying the Robustness of Automatic Credibility Assessment

Verifying the Robustness of Automatic Credibility Assessment

14 March 2023

Piotr Przybyła

Horacio Saggion

Papers citing "Verifying the Robustness of Automatic Credibility Assessment"

10 / 10 papers shown

Title
SoK: Content Moderation in Social Media, from Guidelines to Enforcement, and Research to Practice Mohit Singhal Chen Ling Pujan Paudel Poojitha Thota Nihal Kumarswamy Gianluca Stringhini Shirin Nilizadeh 80 30 0 29 Jun 2022
How Vulnerable Are Automatic Fake News Detection Methods to Adversarial Attacks? Camille Koenders Johannes Filla Nicolai Schneider Vinicius Woloszyn GNN 75 15 0 16 Jul 2021
MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection Models Thai Le Suhang Wang Dongwon Lee 99 59 0 01 Sep 2020
Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment Di Jin Zhijing Jin Qiufeng Wang Peter Szolovits SILM AAML 113 1,064 0 27 Jul 2019
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 359 921 0 21 Apr 2018
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks Mohit Iyyer John Wieting Kevin Gimpel Luke Zettlemoyer AAML GAN 309 715 0 17 Apr 2018
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers Ji Gao Jack Lanchantin M. Soffa Yanjun Qi AAML 109 716 0 13 Jan 2018
This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire than Real News Benjamin D. Horne Sibel Adali GNN 40 586 0 28 Mar 2017
A Stylometric Inquiry into Hyperpartisan and Fake News Martin Potthast Johannes Kiesel K. Reinartz Janek Bevendorff Benno Stein 55 614 0 18 Feb 2017
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 183 14,831 1 21 Dec 2013