NLP Attacks Explained
Jack discusses the intricacies of NLP attacks, emphasizing the importance of transformations, constraints, and goal functions in fooling models. He highlights the potential of using these techniques for data augmentation in NLP, drawing parallels with established practices in computer vision. The conversation reveals exciting opportunities for enhancing model robustness and expanding datasets through innovative approaches.In this clip
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Practical AI
Attack of the C̶l̶o̶n̶e̶s̶ Text!
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