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Related Questions
- What types of adversarial attacks are commonly used to evaluate the robustness of NLP models?
- How do adversarial attacks affect the performance of NLP models in real-world applications?
- Can you explain the difference between white-box and black-box adversarial attacks in the context of NLP models?
- How are saliency maps used to visualize and interpret the results of adversarial attacks on NLP models?
- What are some common metrics used to evaluate the robustness of NLP models to adversarial attacks?
- How can researchers and developers use adversarial attacks to improve the security and reliability of NLP models?
- Are there any limitations or challenges associated with using adversarial attacks to evaluate the robustness of NLP models, and if so, what are they?
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