Papers with ContextuaLized AdversaRial Example generation model
Contextualized Perturbation for Textual Adversarial Attack (2021.naacl-main)
Copied to clipboard
| Challenge: | Existing techniques for generating adversarial examples are driven by local heuristic rules that are agnostic to the context, resulting in unnatural and ungrammatical outputs. |
| Approach: | They propose a ContextuaLized AdversaRial Example generation model that generates fluent and grammatical outputs through a mask-then-infill procedure. |
| Outcome: | The proposed model outperforms baseline models in terms of attack success rate, textual similarity, fluency and grammaticality. |