Identifying Misinformation on YouTube through Transcript Contextual Analysis with Transformer Models

1 code implementation • 22 Jul 2023 • Christos Christodoulou, Nikos Salamanos, Pantelitsa Leonidou, Michail Papadakis, Michael Sirivianos

We apply the trained models to three datasets: (a) YouTube Vaccine-misinformation related videos, (b) YouTube Pseudoscience videos, and (c) Fake-News dataset (a collection of articles).

Few-Shot Learning Misinformation +6

On Evaluating Adversarial Robustness of Chest X-ray Classification: Pitfalls and Best Practices

no code implementations • 15 Dec 2022 • Salah Ghamizi, Maxime Cordy, Michail Papadakis, Yves Le Traon

Vulnerability to adversarial attacks is a well-known weakness of Deep Neural Networks.

Adversarial Robustness Classification +1

MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based Ensembles

no code implementations • 27 Sep 2021 • Yuejun Guo, Qiang Hu, Maxime Cordy, Michail Papadakis, Yves Le Traon

In this paper, we propose MUTEN, a low-cost method to improve the success rate of well-known attacks against gradient-masking models.