Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend
Fuente:
arXiv
Saved in:
| Main Authors: | Lu, Ning, Liu, Shengcai, Zhang, Zhirui, Wang, Qi, Liu, Haifeng, Tang, Ke |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script
by: Cao, Xi, et al.
Published: (2024)
by: Cao, Xi, et al.
Published: (2024)
Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language Model
by: Cao, Xi, et al.
Published: (2024)
by: Cao, Xi, et al.
Published: (2024)
RTD-Guard: A Black-Box Textual Adversarial Detection Framework via Replacement Token Detection
by: Zhu, He, et al.
Published: (2026)
by: Zhu, He, et al.
Published: (2026)
Large Language Models are Good Attackers: Efficient and Stealthy Textual Backdoor Attacks
by: Li, Ziqiang, et al.
Published: (2024)
by: Li, Ziqiang, et al.
Published: (2024)
MPAT: Building Robust Deep Neural Networks against Textual Adversarial Attacks
by: Zhang, Fangyuan, et al.
Published: (2024)
by: Zhang, Fangyuan, 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)
Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets
by: Lu, Ning, et al.
Published: (2025)
by: Lu, Ning, 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)
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)
Less Is More: Sparse and Cooperative Perturbation for Point Cloud Attacks
by: Tang, Keke, et al.
Published: (2025)
by: Tang, Keke, et al.
Published: (2025)
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)
Route to Rome Attack: Directing LLM Routers to Expensive Models via Adversarial Suffix Optimization
by: Tang, Haochun, et al.
Published: (2026)
by: Tang, Haochun, et al.
Published: (2026)
Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs
by: Liu, Fan, et al.
Published: (2024)
by: Liu, Fan, et al.
Published: (2024)
Iron Sharpens Iron: Defending Against Attacks in Machine-Generated Text Detection with Adversarial Training
by: Li, Yuanfan, et al.
Published: (2025)
by: Li, Yuanfan, et al.
Published: (2025)
More Haste, Less Speed: Weaker Single-Layer Watermark Improves Distortion-Free Watermark Ensembles
by: Chen, Ruibo, et al.
Published: (2026)
by: Chen, Ruibo, et al.
Published: (2026)
Efficient and Stealthy Jailbreak Attacks via Adversarial Prompt Distillation from LLMs to SLMs
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Claim-Guided Textual Backdoor Attack for Practical Applications
by: Song, Minkyoo, et al.
Published: (2024)
by: Song, Minkyoo, et al.
Published: (2024)
Less is More: Sparse Watermarking in LLMs with Enhanced Text Quality
by: Hoang, Duy C., et al.
Published: (2024)
by: Hoang, Duy C., et al.
Published: (2024)
A No-Defense Defense Against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More?
by: elShehaby, Mohamed, et al.
Published: (2026)
by: elShehaby, Mohamed, et al.
Published: (2026)
Topic-FlipRAG: Topic-Orientated Adversarial Opinion Manipulation Attacks to Retrieval-Augmented Generation Models
by: Gong, Yuyang, et al.
Published: (2025)
by: Gong, Yuyang, et al.
Published: (2025)
Imposter.AI: Adversarial Attacks with Hidden Intentions towards Aligned Large Language Models
by: Liu, Xiao, et al.
Published: (2024)
by: Liu, Xiao, et al.
Published: (2024)
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)
The Double-edged Sword of LLM-based Data Reconstruction: Understanding and Mitigating Contextual Vulnerability in Word-level Differential Privacy Text Sanitization
by: Meisenbacher, Stephen, et al.
Published: (2025)
by: Meisenbacher, Stephen, et al.
Published: (2025)
Emoti-Attack: Zero-Perturbation Adversarial Attacks on NLP Systems via Emoji Sequences
by: Zhang, Yangshijie
Published: (2025)
by: Zhang, Yangshijie
Published: (2025)
Adversarial Attack on Large Language Models using Exponentiated Gradient Descent
by: Biswas, Sajib, et al.
Published: (2025)
by: Biswas, Sajib, et al.
Published: (2025)
Adversarial Attacks on LLM-as-a-Judge Systems: Insights from Prompt Injections
by: Maloyan, Narek, et al.
Published: (2025)
by: Maloyan, Narek, et al.
Published: (2025)
Semantic-Preserving Adversarial Attacks on LLMs: An Adaptive Greedy Binary Search Approach
by: Zhang, Chong, et al.
Published: (2025)
by: Zhang, Chong, 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)
Adversarial Attacks Against Automated Fact-Checking: A Survey
by: Liu, Fanzhen, et al.
Published: (2025)
by: Liu, Fanzhen, et al.
Published: (2025)
Don't Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models
by: Yu, Zhiyuan, et al.
Published: (2024)
by: Yu, Zhiyuan, et al.
Published: (2024)
Time-Frequency Jointed Imperceptible Adversarial Attack to Brainprint Recognition with Deep Learning Models
by: Yi, Hangjie, et al.
Published: (2024)
by: Yi, Hangjie, 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)
Enhance Robustness of Language Models Against Variation Attack through Graph Integration
by: Xiong, Zi, et al.
Published: (2024)
by: Xiong, Zi, et al.
Published: (2024)
Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors
by: Wang, Tianchun, et al.
Published: (2024)
by: Wang, Tianchun, et al.
Published: (2024)
from Benign import Toxic: Jailbreaking the Language Model via Adversarial Metaphors
by: Yan, Yu, et al.
Published: (2025)
by: Yan, Yu, et al.
Published: (2025)
Security Attacks on LLM-based Code Completion Tools
by: Cheng, Wen, et al.
Published: (2024)
by: Cheng, Wen, 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)
Invisible Adversaries: A Systematic Study of Session Manipulation Attacks on VPNs
by: Yang, Yuxiang, et al.
Published: (2026)
by: Yang, Yuxiang, et al.
Published: (2026)
Model-Agnostic Lifelong LLM Safety via Externalized Attack-Defense Co-Evolution
by: Zhang, Xiaozhe, et al.
Published: (2026)
by: Zhang, Xiaozhe, et al.
Published: (2026)
LexiMark: Robust Watermarking via Lexical Substitutions to Enhance Membership Verification of an LLM's Textual Training Data
by: German, Eyal, et al.
Published: (2025)
by: German, Eyal, et al.
Published: (2025)
Similar Items
-
Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script
by: Cao, Xi, et al.
Published: (2024) -
Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language Model
by: Cao, Xi, et al.
Published: (2024) -
RTD-Guard: A Black-Box Textual Adversarial Detection Framework via Replacement Token Detection
by: Zhu, He, et al.
Published: (2026) -
Large Language Models are Good Attackers: Efficient and Stealthy Textual Backdoor Attacks
by: Li, Ziqiang, et al.
Published: (2024) -
MPAT: Building Robust Deep Neural Networks against Textual Adversarial Attacks
by: Zhang, Fangyuan, et al.
Published: (2024)