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What is Adversarial NLP for Fake News Detection about?

This paper provides a comprehensive overview of recent advancements in natural language processing (NLP) robustness, highlighting the vulnerabilities of NLP systems to adversarial attacks despite their high performance on benchmark datasets. It categorizes various studies on NLP robustness, identifies gaps in existing literature, and suggests future research directions to enhance the robustness of NLP models. The authors argue for a multi-dimensional approach to robustness, encompassing techniques, metrics,

Author

rutujapawar200525

Language

EN