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Adversarial Text

Adversarial Text refers to a specialised text sequence that is designed specifically to influence the prediction of a language model. Generally, Adversarial Text attack are carried out on Large Language Models (LLMs). Research on understanding different adversarial approaches can help us build effective defense mechanisms to detect malicious text input and build robust language models.

Papers

Showing 111114 of 114 papers

TitleStatusHype
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning ClassifiersCode1
DANCin SEQ2SEQ: Fooling Text Classifiers with Adversarial Text Example GenerationCode0
Towards Crafting Text Adversarial Samples0
Generative Adversarial Text to Image SynthesisCode1
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