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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

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Showing 51–75 of 114 papers

TitleStatusHype
TextDefense: Adversarial Text Detection based on Word Importance Entropy—0
Step by Step Loss Goes Very Far: Multi-Step Quantization for Adversarial Text AttacksCode0
RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation With Natural PromptsCode1
A survey on text generation using generative adversarial networks—0
Ignore Previous Prompt: Attack Techniques For Language ModelsCode2
TAPE: Assessing Few-shot Russian Language UnderstandingCode0
PARSE: An Efficient Search Method for Black-box Adversarial Text Attacks—0
Adversarial Text Normalization—0
SemAttack: Natural Textual Attacks via Different Semantic SpacesCode1
“That Is a Suspicious Reaction!”: Interpreting Logits Variation to Detect NLP Adversarial Attacks—0
Detecting Word-Level Adversarial Text Attacks via SHapley Additive exPlanations—0
"That Is a Suspicious Reaction!": Interpreting Logits Variation to Detect NLP Adversarial AttacksCode1
Adversarial Robustness of Neural-Statistical Features in Detection of Generative TransformersCode0
Data-Driven Mitigation of Adversarial Text Perturbation—0
Identifying Adversarial Attacks on Text Classifiers—0
SemAttack: Natural Textual Attacks via Different Semantic Spaces—0
Repairing Adversarial Texts through Perturbation—0
"That Is a Suspicious Reaction!": Interpreting Logits Variation to Detect NLP Adversarial Attacks—0
Improving Adversarial Text Generation with n-Gram Matching—0
What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations—0
Don’t Search for a Search Method — Simple Heuristics Suffice for Adversarial Text Attacks—0
Generating Watermarked Adversarial Texts—0
SEPP: Similarity Estimation of Predicted Probabilities for Defending and Detecting Adversarial TextCode0
Adversarial Training: A simple and efficient technique to Improving NLP Robustness—0
Don't Search for a Search Method -- Simple Heuristics Suffice for Adversarial Text Attacks—0
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