Cover Image

LimeAttack: Local Explainable Method for Textual Hard-Label Adversarial Attack

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhu, Hai, Yang, Zhaoqing, Shang, Weiwei, Wu, Yuren
Format:	Preprint
Published:	2023
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fast Adversarial Training against Textual Adversarial Attacks
by: Yang, Yichen, et al.
Published: (2024)

HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text
by: Liu, Han, et al.
Published: (2024)

The Best Defense is Attack: Repairing Semantics in Textual Adversarial Examples
by: Yang, Heng, et al.
Published: (2023)

Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language Model
by: Cao, Xi, et al.
Published: (2024)

SEP-Attack: A Simple and Effective Paradigm for Transfer-Based Textual Adversarial Attack
by: Liu, Han, et al.
Published: (2026)

PivotAttack: Rethinking the Search Trajectory in Hard-Label Text Attacks via Pivot Words
by: Liang, Yuzhi, et al.
Published: (2026)

TF-Attack: Transferable and Fast Adversarial Attacks on Large Language Models
by: Li, Zelin, et al.
Published: (2024)

On the Robustness of Verbal Confidence of LLMs in Adversarial Attacks
by: Obadinma, Stephen, et al.
Published: (2025)

Exploring Gradient-Guided Masked Language Model to Detect Textual Adversarial Attacks
by: Zhang, Xiaomei, et al.
Published: (2025)

MPAT: Building Robust Deep Neural Networks against Textual Adversarial Attacks
by: Zhang, Fangyuan, et al.
Published: (2024)

Adversarial Attacks and Defense for Conversation Entailment Task
by: Yang, Zhenning, et al.
Published: (2024)

Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks
by: Zhang, Xinyu, et al.
Published: (2023)

Defense Against Syntactic Textual Backdoor Attacks with Token Substitution
by: Li, Xinglin, et al.
Published: (2024)

Rethinking Targeted Adversarial Attacks For Neural Machine Translation
by: Wu, Junjie, et al.
Published: (2024)

Breaking the Reviewer: Assessing the Vulnerability of Large Language Models in Automated Peer Review Under Textual Adversarial Attacks
by: Lin, Tzu-Ling, et al.
Published: (2025)

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)

GenFighter: A Generative and Evolutive Textual Attack Removal
by: Islam, Md Athikul, et al.
Published: (2024)

SEMA: Simple yet Effective Learning for Multi-Turn Jailbreak Attacks
by: Feng, Mingqian, et al.
Published: (2026)

Adversarial Attack for Explanation Robustness of Rationalization Models
by: Zhang, Yuankai, et al.
Published: (2024)

Enhancing Adversarial Attacks through Chain of Thought
by: Su, Jingbo
Published: (2024)

Reversible Jump Attack to Textual Classifiers with Modification Reduction
by: Ni, Mingze, et al.
Published: (2024)

Claim-Guided Textual Backdoor Attack for Practical Applications
by: Song, Minkyoo, 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)

Context-aware Adversarial Attack on Named Entity Recognition
by: Chen, Shuguang, et al.
Published: (2023)

Robustness of Large Language Models Against Adversarial Attacks
by: Tao, Yiyi, et al.
Published: (2024)

Semantic Stealth: Adversarial Text Attacks on NLP Using Several Methods
by: Dey, Roopkatha, et al.
Published: (2024)

Large Language Models are Good Attackers: Efficient and Stealthy Textual Backdoor Attacks
by: Li, Ziqiang, et al.
Published: (2024)

STACK: Adversarial Attacks on LLM Safeguard Pipelines
by: McKenzie, Ian R., et al.
Published: (2025)

Combating Adversarial Attacks with Multi-Agent Debate
by: Chern, Steffi, et al.
Published: (2024)

Adversarial Attacks Against Automated Fact-Checking: A Survey
by: Liu, Fanzhen, et al.
Published: (2025)

X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
by: Huang, Hanxun, et al.
Published: (2025)

Adversarial Confusion Attack: Disrupting Multimodal Large Language Models
by: Hoscilowicz, Jakub, et al.
Published: (2025)

A Constraint-Enforcing Reward for Adversarial Attacks on Text Classifiers
by: Roth, Tom, et al.
Published: (2024)

Seeing the Threat: Vulnerabilities in Vision-Language Models to Adversarial Attack
by: Ren, Juan, et al.
Published: (2025)

Revisiting Character-level Adversarial Attacks for Language Models
by: Rocamora, Elias Abad, et al.
Published: (2024)

MultiAgent Collaboration Attack: Investigating Adversarial Attacks in Large Language Model Collaborations via Debate
by: Amayuelas, Alfonso, et al.
Published: (2024)

Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks
by: Yang, Hunmin, et al.
Published: (2024)

OpenFact at CheckThat! 2024: Combining Multiple Attack Methods for Effective Adversarial Text Generation
by: Lewoniewski, Włodzimierz, et al.
Published: (2024)

Zero2Text: Zero-Training Cross-Domain Inversion Attacks on Textual Embeddings
by: Kim, Doohyun, et al.
Published: (2026)

Based on Data Balancing and Model Improvement for Multi-Label Sentiment Classification Performance Enhancement
by: Su, Zijin, et al.
Published: (2025)