Learnable Privacy Neurons Localization in Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Ruizhe, Hu, Tianxiang, Feng, Yang, Liu, Zuozhu |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks
by: Chen, Xiaoyi, et al.
Published: (2023)
by: Chen, Xiaoyi, et al.
Published: (2023)
Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation
by: Li, Xianzhi, et al.
Published: (2024)
by: Li, Xianzhi, et al.
Published: (2024)
DP-MemArc: Differential Privacy Transfer Learning for Memory Efficient Language Models
by: Liu, Yanming, et al.
Published: (2024)
by: Liu, Yanming, et al.
Published: (2024)
Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning
by: Li, Jianwei, et al.
Published: (2023)
by: Li, Jianwei, et al.
Published: (2023)
Preserving Privacy in Large Language Models: A Survey on Current Threats and Solutions
by: Miranda, Michele, et al.
Published: (2024)
by: Miranda, Michele, et al.
Published: (2024)
Privacy-Preserving Data Deduplication for Enhancing Federated Learning of Language Models (Extended Version)
by: Abadi, Aydin, et al.
Published: (2024)
by: Abadi, Aydin, et al.
Published: (2024)
HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection
by: Wang, Yuxin, et al.
Published: (2024)
by: Wang, Yuxin, et al.
Published: (2024)
Reconstruct Your Previous Conversations! Comprehensively Investigating Privacy Leakage Risks in Conversations with GPT Models
by: Chu, Junjie, et al.
Published: (2024)
by: Chu, Junjie, et al.
Published: (2024)
Do Phone-Use Agents Respect Your Privacy?
by: Tang, Zhengyang, et al.
Published: (2026)
by: Tang, Zhengyang, et al.
Published: (2026)
Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes
by: Hu, Xiaomeng, et al.
Published: (2024)
by: Hu, Xiaomeng, et al.
Published: (2024)
Mark Your LLM: Detecting the Misuse of Open-Source Large Language Models via Watermarking
by: Xu, Yijie, et al.
Published: (2025)
by: Xu, Yijie, et al.
Published: (2025)
Virus: Harmful Fine-tuning Attack for Large Language Models Bypassing Guardrail Moderation
by: Huang, Tiansheng, et al.
Published: (2025)
by: Huang, Tiansheng, et al.
Published: (2025)
Securing Multi-turn Conversational Language Models From Distributed Backdoor Triggers
by: Tong, Terry, et al.
Published: (2024)
by: Tong, Terry, et al.
Published: (2024)
Large Language Models in Cybersecurity: State-of-the-Art
by: Motlagh, Farzad Nourmohammadzadeh, et al.
Published: (2024)
by: Motlagh, Farzad Nourmohammadzadeh, et al.
Published: (2024)
OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models
by: Xu, Xiaoyu, et al.
Published: (2025)
by: Xu, Xiaoyu, et al.
Published: (2025)
The Resurgence of GCG Adversarial Attacks on Large Language Models
by: Tan, Yuting, et al.
Published: (2025)
by: Tan, Yuting, et al.
Published: (2025)
Duwak: Dual Watermarks in Large Language Models
by: Zhu, Chaoyi, et al.
Published: (2024)
by: Zhu, Chaoyi, et al.
Published: (2024)
Position: Privacy Is Not Just Memorization!
by: Mireshghallah, Niloofar, et al.
Published: (2025)
by: Mireshghallah, Niloofar, et al.
Published: (2025)
On the Role of Attention Heads in Large Language Model Safety
by: Zhou, Zhenhong, et al.
Published: (2024)
by: Zhou, Zhenhong, et al.
Published: (2024)
Detecting Training Data of Large Language Models via Expectation Maximization
by: Kim, Gyuwan, et al.
Published: (2024)
by: Kim, Gyuwan, et al.
Published: (2024)
MetaMoE: Diversity-Aware Proxy Selection for Privacy-Preserving Mixture-of-Experts Unification
by: Jiang, Weisen, et al.
Published: (2026)
by: Jiang, Weisen, et al.
Published: (2026)
Instructional Fingerprinting of Large Language Models
by: Xu, Jiashu, et al.
Published: (2024)
by: Xu, Jiashu, et al.
Published: (2024)
FIT to Forget: Robust Continual Unlearning for Large Language Models
by: Xu, Xiaoyu, et al.
Published: (2026)
by: Xu, Xiaoyu, et al.
Published: (2026)
Unlocking Memorization in Large Language Models with Dynamic Soft Prompting
by: Wang, Zhepeng, et al.
Published: (2024)
by: Wang, Zhepeng, et al.
Published: (2024)
Directional Embedding Smoothing for Robust Vision Language Models
by: Wang, Ye, et al.
Published: (2026)
by: Wang, Ye, et al.
Published: (2026)
Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion
by: Wang, Guanchu, et al.
Published: (2024)
by: Wang, Guanchu, et al.
Published: (2024)
Towards Robust Knowledge Unlearning: An Adversarial Framework for Assessing and Improving Unlearning Robustness in Large Language Models
by: Yuan, Hongbang, et al.
Published: (2024)
by: Yuan, Hongbang, et al.
Published: (2024)
Probing the Robustness of Large Language Models Safety to Latent Perturbations
by: Gu, Tianle, et al.
Published: (2025)
by: Gu, Tianle, et al.
Published: (2025)
Special Characters Attack: Toward Scalable Training Data Extraction From Large Language Models
by: Bai, Yang, et al.
Published: (2024)
by: Bai, Yang, et al.
Published: (2024)
MANATEE: Inference-Time Lightweight Diffusion Based Safety Defense for LLMs
by: Kan, Chun Yan Ryan, et al.
Published: (2026)
by: Kan, Chun Yan Ryan, et al.
Published: (2026)
SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models
by: Li, Lijun, et al.
Published: (2024)
by: Li, Lijun, et al.
Published: (2024)
Trustworthy AI: Safety, Bias, and Privacy -- A Survey
by: Fang, Xingli, et al.
Published: (2025)
by: Fang, Xingli, et al.
Published: (2025)
On the Learnability of Watermarks for Language Models
by: Gu, Chenchen, et al.
Published: (2023)
by: Gu, Chenchen, et al.
Published: (2023)
Adversarial Text Purification: A Large Language Model Approach for Defense
by: Moraffah, Raha, et al.
Published: (2024)
by: Moraffah, Raha, et al.
Published: (2024)
Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting
by: Liu, Fuqiang, et al.
Published: (2024)
by: Liu, Fuqiang, et al.
Published: (2024)
Teach LLMs to Phish: Stealing Private Information from Language Models
by: Panda, Ashwinee, et al.
Published: (2024)
by: Panda, Ashwinee, et al.
Published: (2024)
How Private is Your Attention? Bridging Privacy with In-Context Learning
by: Bonnerjee, Soham, et al.
Published: (2025)
by: Bonnerjee, Soham, et al.
Published: (2025)
Instructions as Backdoors: Backdoor Vulnerabilities of Instruction Tuning for Large Language Models
by: Xu, Jiashu, et al.
Published: (2023)
by: Xu, Jiashu, et al.
Published: (2023)
EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage
by: Liao, Zeyi, et al.
Published: (2024)
by: Liao, Zeyi, et al.
Published: (2024)
Faster-GCG: Efficient Discrete Optimization Jailbreak Attacks against Aligned Large Language Models
by: Li, Xiao, et al.
Published: (2024)
by: Li, Xiao, et al.
Published: (2024)
Similar Items
-
The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks
by: Chen, Xiaoyi, et al.
Published: (2023) -
Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation
by: Li, Xianzhi, et al.
Published: (2024) -
DP-MemArc: Differential Privacy Transfer Learning for Memory Efficient Language Models
by: Liu, Yanming, et al.
Published: (2024) -
Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning
by: Li, Jianwei, et al.
Published: (2023) -
Preserving Privacy in Large Language Models: A Survey on Current Threats and Solutions
by: Miranda, Michele, et al.
Published: (2024)