Saved in:
| Main Authors: | Chen, Zhiyu, Li, Yu, Zhang, Suochao, Zhou, Jingbo, Zhou, Jiwen, Bao, Chenfu, Yu, Dianhai |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.07283 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Enhancing Adversarial Attacks via Parameter Adaptive Adversarial Attack
by: Jin, Zhibo, et al.
Published: (2024)
by: Jin, Zhibo, et al.
Published: (2024)
Robust LLM safeguarding via refusal feature adversarial training
by: Yu, Lei, et al.
Published: (2024)
by: Yu, Lei, et al.
Published: (2024)
Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets
by: Hsiung, Lei, et al.
Published: (2025)
by: Hsiung, Lei, et al.
Published: (2025)
Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors
by: Wang, Tianchun, et al.
Published: (2024)
by: Wang, Tianchun, et al.
Published: (2024)
Adaptive Instruction Composition for Automated LLM Red-Teaming
by: Zymet, Jesse, et al.
Published: (2026)
by: Zymet, Jesse, et al.
Published: (2026)
Low-Cost Hard-Label Adversarial Attack with Theoretical Foundations
by: Liu, Jun, et al.
Published: (2026)
by: Liu, Jun, et al.
Published: (2026)
Attack and defense techniques in large language models: A survey and new perspectives
by: Liao, Zhiyu, et al.
Published: (2025)
by: Liao, Zhiyu, et al.
Published: (2025)
Assessing Deanonymization Risks with Stylometry-Assisted LLM Agent
by: Zhang, Boyang, et al.
Published: (2026)
by: Zhang, Boyang, et al.
Published: (2026)
WaterVIB: Learning Minimal Sufficient Watermark Representations via Variational Information Bottleneck
by: He, Haoyuan, et al.
Published: (2026)
by: He, Haoyuan, et al.
Published: (2026)
LLM Unlearning Should Be Form-Independent
by: Ye, Xiaotian, et al.
Published: (2025)
by: Ye, Xiaotian, et al.
Published: (2025)
MPAT: Building Robust Deep Neural Networks against Textual Adversarial Attacks
by: Zhang, Fangyuan, et al.
Published: (2024)
by: Zhang, Fangyuan, et al.
Published: (2024)
PVMark: Enabling Public Verifiability for LLM Watermarking Schemes
by: Duan, Haohua, et al.
Published: (2025)
by: Duan, Haohua, et al.
Published: (2025)
What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference
by: Fan, Mingyuan, et al.
Published: (2026)
by: Fan, Mingyuan, et al.
Published: (2026)
Panther: A Cost-Effective Privacy-Preserving Framework for GNN Training and Inference Services in Cloud Environments
by: Chen, Congcong, et al.
Published: (2025)
by: Chen, Congcong, et al.
Published: (2025)
Adaptive Pre-training Data Detection for Large Language Models via Surprising Tokens
by: Zhang, Anqi, et al.
Published: (2024)
by: Zhang, Anqi, et al.
Published: (2024)
InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy
by: Vinod, Vishnu, et al.
Published: (2025)
by: Vinod, Vishnu, et al.
Published: (2025)
LLM Ghostbusters: Surgical Hallucination Suppression via Adaptive Unlearning
by: Spracklen, Joseph, et al.
Published: (2026)
by: Spracklen, Joseph, et al.
Published: (2026)
Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation
by: Chen, Sixu, et al.
Published: (2026)
by: Chen, Sixu, et al.
Published: (2026)
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)
VERA: Variational Inference Framework for Jailbreaking Large Language Models
by: Lochab, Anamika, et al.
Published: (2025)
by: Lochab, Anamika, et al.
Published: (2025)
AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
by: Zeng, Yifan, et al.
Published: (2024)
by: Zeng, Yifan, et al.
Published: (2024)
FreqMark: Frequency-Based Watermark for Sentence-Level Detection of LLM-Generated Text
by: Xu, Zhenyu, et al.
Published: (2024)
by: Xu, Zhenyu, et al.
Published: (2024)
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)
The Hidden Cost of Modeling P(X): Vulnerability to Membership Inference Attacks in Generative Text Classifiers
by: Makroo, Owais, et al.
Published: (2025)
by: Makroo, Owais, et al.
Published: (2025)
SecFormer: Fast and Accurate Privacy-Preserving Inference for Transformer Models via SMPC
by: Luo, Jinglong, et al.
Published: (2024)
by: Luo, Jinglong, et al.
Published: (2024)
The Landscape of Memorization in LLMs: Mechanisms, Measurement, and Mitigation
by: Xiong, Alexander, et al.
Published: (2025)
by: Xiong, Alexander, et al.
Published: (2025)
GCG Attack On A Diffusion LLM
by: Neyroud, Ruben, et al.
Published: (2025)
by: Neyroud, Ruben, et al.
Published: (2025)
On the Effectiveness of Membership Inference in Targeted Data Extraction from Large Language Models
by: Sahili, Ali Al, et al.
Published: (2025)
by: Sahili, Ali Al, et al.
Published: (2025)
Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy
by: Wu, Tong, et al.
Published: (2024)
by: Wu, Tong, et al.
Published: (2024)
A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
by: Wang, Kun, et al.
Published: (2025)
by: Wang, Kun, et al.
Published: (2025)
FGAD: Self-boosted Knowledge Distillation for An Effective Federated Graph Anomaly Detection Framework
by: Cai, Jinyu, et al.
Published: (2024)
by: Cai, Jinyu, et al.
Published: (2024)
A Fast, Reliable, and Secure Programming Language for LLM Agents with Code Actions
by: Mell, Stephen, et al.
Published: (2025)
by: Mell, Stephen, 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)
Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk
by: Li, Zhangheng, et al.
Published: (2024)
by: Li, Zhangheng, et al.
Published: (2024)
LLMGuard: Guarding Against Unsafe LLM Behavior
by: Goyal, Shubh, et al.
Published: (2024)
by: Goyal, Shubh, et al.
Published: (2024)
Sparse Autoencoders are Capable LLM Jailbreak Mitigators
by: Assogba, Yannick, et al.
Published: (2026)
by: Assogba, Yannick, et al.
Published: (2026)
Localizing Malicious Outputs from CodeLLM
by: Borana, Mayukh, et al.
Published: (2025)
by: Borana, Mayukh, 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)
Copyright-Protected Language Generation via Adaptive Model Fusion
by: Abad, Javier, et al.
Published: (2024)
by: Abad, Javier, et al.
Published: (2024)
TurboFuzzLLM: Turbocharging Mutation-based Fuzzing for Effectively Jailbreaking Large Language Models in Practice
by: Goel, Aman, et al.
Published: (2025)
by: Goel, Aman, et al.
Published: (2025)
Similar Items
-
Enhancing Adversarial Attacks via Parameter Adaptive Adversarial Attack
by: Jin, Zhibo, et al.
Published: (2024) -
Robust LLM safeguarding via refusal feature adversarial training
by: Yu, Lei, et al.
Published: (2024) -
Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets
by: Hsiung, Lei, et al.
Published: (2025) -
Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors
by: Wang, Tianchun, et al.
Published: (2024) -
Adaptive Instruction Composition for Automated LLM Red-Teaming
by: Zymet, Jesse, et al.
Published: (2026)