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Adversarial Data Poisoning for Fake News Detection: How to Make a Model
  Misclassify a Target News without Modifying It
v1v2 (latest)

Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News without Modifying It

23 December 2023
F. Siciliano
Luca Maiano
Lorenzo Papa
Federica Baccin
Irene Amerini
Fabrizio Silvestri
    AAML
ArXiv (abs)PDFHTML

Papers citing "Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News without Modifying It"

1 / 1 papers shown
Title
Fraud-R1 : A Multi-Round Benchmark for Assessing the Robustness of LLM Against Augmented Fraud and Phishing Inducements
Fraud-R1 : A Multi-Round Benchmark for Assessing the Robustness of LLM Against Augmented Fraud and Phishing Inducements
Shu Yang
Shenzhe Zhu
Zeyu Wu
Keyu Wang
Junchi Yao
Junchao Wu
Lijie Hu
Mengdi Li
Derek F. Wong
Di Wang
75
9
0
18 Feb 2025
1