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The ERINIA project investigates the robustness of text classifiers against adversarial examples in the context of misinformation detection. By exploring methods such as reinforcement learning and style transfer, the project aims to enhance the reliability of tools that identify fake news and propaganda techniques.
As challenges posed by misinformation become apparent in the modern digital society, state-of-the-art methods of Artificial Intelligence, especially Natural Language Processing (NLP) and Machine Learning, are considered as countermeasures.
Indeed, previous research has shown that NLP solutions can detect phenomena such as fake news, social media bots or usage of propaganda techniques.
However, little attention has been given to the robustness of these approaches, which is especially important in…
UNIVERSIDAD POMPEU FABRA
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