XVD: Cross-Vocabulary Differentiable Training for Generative Adversarial Attacks (2024.lrec-main)
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| Challenge: | Existing approaches to create adversarial examples using tokens are not sufficient to ensure other desirable properties such as similarity to non-adversarial examples, linguistic fluency, and so forth. |
| Approach: | They propose a method which leverages a set of pretrained language models to promote similarity to non-adversarial examples, linguistic fluency, and so forth. |
| Outcome: | The proposed approach outperforms existing methods and is competitive with token-based approaches. |
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| Challenge: | Adversarial training is widely acknowledged as the most effective defense against adversarial attacks, but achieving both robustness and generalization requires a trade-off. |
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Adversarial Text Generation by Search and Learning (2023.findings-emnlp)
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Guoyi Li, Bingkang Shi, Zongzhen Liu, Dehan Kong, Yulei Wu, Xiaodan Zhang, Longtao Huang, Honglei Lyu
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