MPAT: Building Robust Deep Neural Networks against Textual Adversarial Attacks
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Fangyuan, Zhou, Huichi, Li, Shuangjiao, Wang, Hongtao |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks
by: Zhang, Xinyu, et al.
Published: (2023)
by: Zhang, Xinyu, et al.
Published: (2023)
A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models
by: Dang, Cuong, et al.
Published: (2024)
by: Dang, Cuong, et al.
Published: (2024)
Bits Leaked per Query: Information-Theoretic Bounds on Adversarial Attacks against LLMs
by: Kaneko, Masahiro, et al.
Published: (2025)
by: Kaneko, Masahiro, et al.
Published: (2025)
Reversible Jump Attack to Textual Classifiers with Modification Reduction
by: Ni, Mingze, et al.
Published: (2024)
by: Ni, Mingze, et al.
Published: (2024)
Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend
by: Lu, Ning, et al.
Published: (2023)
by: Lu, Ning, et al.
Published: (2023)
Steering Dialogue Dynamics for Robustness against Multi-turn Jailbreaking Attacks
by: Hu, Hanjiang, et al.
Published: (2025)
by: Hu, Hanjiang, et al.
Published: (2025)
PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
by: Zhu, Kaijie, et al.
Published: (2023)
by: Zhu, Kaijie, et al.
Published: (2023)
AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
by: Zeng, Yifan, et al.
Published: (2024)
by: Zeng, Yifan, et al.
Published: (2024)
Humanizing Machine-Generated Content: Evading AI-Text Detection through Adversarial Attack
by: Zhou, Ying, et al.
Published: (2024)
by: Zhou, Ying, et al.
Published: (2024)
Deciphering the Chaos: Enhancing Jailbreak Attacks via Adversarial Prompt Translation
by: Li, Qizhang, et al.
Published: (2024)
by: Li, Qizhang, et al.
Published: (2024)
IDT: Dual-Task Adversarial Attacks for Privacy Protection
by: Faustini, Pedro, et al.
Published: (2024)
by: Faustini, Pedro, et al.
Published: (2024)
Towards More Realistic Extraction Attacks: An Adversarial Perspective
by: More, Yash, et al.
Published: (2024)
by: More, Yash, et al.
Published: (2024)
Watch Out for Your Guidance on Generation! Exploring Conditional Backdoor Attacks against Large Language Models
by: He, Jiaming, et al.
Published: (2024)
by: He, Jiaming, et al.
Published: (2024)
Self-Evaluation as a Defense Against Adversarial Attacks on LLMs
by: Brown, Hannah, et al.
Published: (2024)
by: Brown, Hannah, et al.
Published: (2024)
MARAGE: Transferable Multi-Model Adversarial Attack for Retrieval-Augmented Generation Data Extraction
by: Hu, Xiao, et al.
Published: (2025)
by: Hu, Xiao, et al.
Published: (2025)
Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration
by: Fu, Wenjie, et al.
Published: (2023)
by: Fu, Wenjie, et al.
Published: (2023)
Revisiting the Robustness of Watermarking to Paraphrasing Attacks
by: Rastogi, Saksham, et al.
Published: (2024)
by: Rastogi, Saksham, et al.
Published: (2024)
Semantic Stealth: Adversarial Text Attacks on NLP Using Several Methods
by: Dey, Roopkatha, et al.
Published: (2024)
by: Dey, Roopkatha, et al.
Published: (2024)
Enhancing Adversarial Text Attacks on BERT Models with Projected Gradient Descent
by: Waghela, Hetvi, et al.
Published: (2024)
by: Waghela, Hetvi, et al.
Published: (2024)
Adversarial Attack on Large Language Models using Exponentiated Gradient Descent
by: Biswas, Sajib, et al.
Published: (2025)
by: Biswas, Sajib, et al.
Published: (2025)
Token-Modification Adversarial Attacks for Natural Language Processing: A Survey
by: Roth, Tom, et al.
Published: (2021)
by: Roth, Tom, et al.
Published: (2021)
Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
by: Liang, Zi, et al.
Published: (2025)
by: Liang, Zi, et al.
Published: (2025)
Certifiably Robust RAG against Retrieval Corruption
by: Xiang, Chong, et al.
Published: (2024)
by: Xiang, Chong, et al.
Published: (2024)
Defending against Backdoor Attack on Deep Neural Networks
by: Cheng, Hao, et al.
Published: (2020)
by: Cheng, Hao, et al.
Published: (2020)
A Modified Word Saliency-Based Adversarial Attack on Text Classification Models
by: Waghela, Hetvi, et al.
Published: (2024)
by: Waghela, Hetvi, et al.
Published: (2024)
Attack by Unlearning: Unlearning-Induced Adversarial Attacks on Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2026)
by: Zhang, Jiahao, et al.
Published: (2026)
DocMIA: Document-Level Membership Inference Attacks against DocVQA Models
by: Nguyen, Khanh, et al.
Published: (2025)
by: Nguyen, Khanh, et al.
Published: (2025)
Adversarial Decoding: Generating Readable Documents for Adversarial Objectives
by: Zhang, Collin, et al.
Published: (2024)
by: Zhang, Collin, et al.
Published: (2024)
CR-UTP: Certified Robustness against Universal Text Perturbations on Large Language Models
by: Lou, Qian, et al.
Published: (2024)
by: Lou, Qian, et al.
Published: (2024)
Certifying LLM Safety against Adversarial Prompting
by: Kumar, Aounon, et al.
Published: (2023)
by: Kumar, Aounon, et al.
Published: (2023)
The Resurgence of GCG Adversarial Attacks on Large Language Models
by: Tan, Yuting, et al.
Published: (2025)
by: Tan, Yuting, et al.
Published: (2025)
Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval
by: Chen, Taiye, et al.
Published: (2025)
by: Chen, Taiye, et al.
Published: (2025)
Towards Building a Robust Toxicity Predictor
by: Bespalov, Dmitriy, et al.
Published: (2024)
by: Bespalov, Dmitriy, et al.
Published: (2024)
Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data
by: Simonetto, Thibault, et al.
Published: (2024)
by: Simonetto, Thibault, et al.
Published: (2024)
On the Robustness of Bayesian Neural Networks to Adversarial Attacks
by: Bortolussi, Luca, et al.
Published: (2022)
by: Bortolussi, Luca, et al.
Published: (2022)
HSF: Defending against Jailbreak Attacks with Hidden State Filtering
by: Qian, Cheng, et al.
Published: (2024)
by: Qian, Cheng, et al.
Published: (2024)
LARGO: Latent Adversarial Reflection through Gradient Optimization for Jailbreaking LLMs
by: Li, Ran, et al.
Published: (2025)
by: Li, Ran, et al.
Published: (2025)
Subspace Defense: Discarding Adversarial Perturbations by Learning a Subspace for Clean Signals
by: Zheng, Rui, et al.
Published: (2024)
by: Zheng, Rui, et al.
Published: (2024)
A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-level Privacy Leakage
by: Xin, Rui, et al.
Published: (2025)
by: Xin, Rui, et al.
Published: (2025)
On Evaluating The Performance of Watermarked Machine-Generated Texts Under Adversarial Attacks
by: Liu, Zesen, et al.
Published: (2024)
by: Liu, Zesen, et al.
Published: (2024)
Similar Items
-
Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks
by: Zhang, Xinyu, et al.
Published: (2023) -
A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models
by: Dang, Cuong, et al.
Published: (2024) -
Bits Leaked per Query: Information-Theoretic Bounds on Adversarial Attacks against LLMs
by: Kaneko, Masahiro, et al.
Published: (2025) -
Reversible Jump Attack to Textual Classifiers with Modification Reduction
by: Ni, Mingze, et al.
Published: (2024) -
Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend
by: Lu, Ning, et al.
Published: (2023)