Privacy-Aware Decoding: Mitigating Privacy Leakage of Large Language Models in Retrieval-Augmented Generation
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Haoran, Xu, Xiongxiao, Huang, Baixiang, Shu, Kai |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Can Knowledge Editing Really Correct Hallucinations?
by: Huang, Baixiang, et al.
Published: (2024)
by: Huang, Baixiang, et al.
Published: (2024)
Can Large Language Models Identify Authorship?
by: Huang, Baixiang, et al.
Published: (2024)
by: Huang, Baixiang, et al.
Published: (2024)
Understanding and Mitigating Cross-lingual Privacy Leakage via Language-specific and Universal Privacy Neurons
by: Dong, Wenshuo, et al.
Published: (2025)
by: Dong, Wenshuo, et al.
Published: (2025)
Sanitize Your Responses: Mitigating Privacy Leakage in Large Language Models
by: Fu, Wenjie, et al.
Published: (2025)
by: Fu, Wenjie, et al.
Published: (2025)
Do LLMs Know What Is Private Internally? Probing and Steering Contextual Privacy Norms in Large Language Model Representations
by: Wang, Haoran, et al.
Published: (2026)
by: Wang, Haoran, et al.
Published: (2026)
Estimating Privacy Leakage of Augmented Contextual Knowledge in Language Models
by: Flemings, James, et al.
Published: (2024)
by: Flemings, James, et al.
Published: (2024)
PATCH: Mitigating PII Leakage in Language Models with Privacy-Aware Targeted Circuit PatcHing
by: Hughes, Anthony, et al.
Published: (2025)
by: Hughes, Anthony, et al.
Published: (2025)
SoK: Privacy Risks and Mitigations in Retrieval-Augmented Generation Systems
by: Bodea, Andreea-Elena, et al.
Published: (2026)
by: Bodea, Andreea-Elena, et al.
Published: (2026)
Language Drift in Multilingual Retrieval-Augmented Generation: Characterization and Decoding-Time Mitigation
by: Li, Bo, et al.
Published: (2025)
by: Li, Bo, et al.
Published: (2025)
Privacy-Preserving Retrieval-Augmented Generation with Differential Privacy
by: Koga, Tatsuki, et al.
Published: (2024)
by: Koga, Tatsuki, et al.
Published: (2024)
Quantifying Association Capabilities of Large Language Models and Its Implications on Privacy Leakage
by: Shao, Hanyin, et al.
Published: (2023)
by: Shao, Hanyin, et al.
Published: (2023)
Can Multimodal LLMs Perform Time Series Anomaly Detection?
by: Xu, Xiongxiao, et al.
Published: (2025)
by: Xu, Xiongxiao, et al.
Published: (2025)
Privacy-protected Retrieval-Augmented Generation for Knowledge Graph Question Answering
by: Ning, Yunfeng, et al.
Published: (2025)
by: Ning, Yunfeng, et al.
Published: (2025)
Comparing Retrieval-Augmentation and Parameter-Efficient Fine-Tuning for Privacy-Preserving Personalization of Large Language Models
by: Salemi, Alireza, et al.
Published: (2024)
by: Salemi, Alireza, et al.
Published: (2024)
Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation
by: Mao, Qianren, et al.
Published: (2025)
by: Mao, Qianren, et al.
Published: (2025)
Entropy-Based Decoding for Retrieval-Augmented Large Language Models
by: Qiu, Zexuan, et al.
Published: (2024)
by: Qiu, Zexuan, et al.
Published: (2024)
Equipping Retrieval-Augmented Large Language Models with Document Structure Awareness
by: Xu, Lingnan, et al.
Published: (2025)
by: Xu, Lingnan, et al.
Published: (2025)
Privacy-Preserving Reasoning with Knowledge-Distilled Parametric Retrieval Augmented Generation
by: Chen, Jinwen, et al.
Published: (2025)
by: Chen, Jinwen, et al.
Published: (2025)
Privacy in Large Language Models: Attacks, Defenses and Future Directions
by: Li, Haoran, et al.
Published: (2023)
by: Li, Haoran, et al.
Published: (2023)
Piecing It All Together: Verifying Multi-Hop Multimodal Claims
by: Wang, Haoran, et al.
Published: (2024)
by: Wang, Haoran, et al.
Published: (2024)
Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language Models
by: Li, Mingda, et al.
Published: (2024)
by: Li, Mingda, et al.
Published: (2024)
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)
by: Zeng, Shenglai, et al.
Published: (2024)
by: Zeng, Shenglai, et al.
Published: (2024)
Evaluation of Attribution Bias in Generator-Aware Retrieval-Augmented Large Language Models
by: Abolghasemi, Amin, et al.
Published: (2024)
by: Abolghasemi, Amin, et al.
Published: (2024)
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)
Trojan Activation Attack: Red-Teaming Large Language Models using Activation Steering for Safety-Alignment
by: Wang, Haoran, et al.
Published: (2023)
by: Wang, Haoran, et al.
Published: (2023)
Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey
by: Gan, Aoran, et al.
Published: (2025)
by: Gan, Aoran, et al.
Published: (2025)
Towards Effective Model Editing for LLM Personalization
by: Huang, Baixiang, et al.
Published: (2025)
by: Huang, Baixiang, et al.
Published: (2025)
M-RAG: Reinforcing Large Language Model Performance through Retrieval-Augmented Generation with Multiple Partitions
by: Wang, Zheng, et al.
Published: (2024)
by: Wang, Zheng, et al.
Published: (2024)
GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory
by: Fan, Wei, et al.
Published: (2024)
by: Fan, Wei, et al.
Published: (2024)
Model Editing as a Double-Edged Sword: Steering Agent Ethical Behavior Toward Beneficence or Harm
by: Huang, Baixiang, et al.
Published: (2025)
by: Huang, Baixiang, et al.
Published: (2025)
PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action
by: Shao, Yijia, et al.
Published: (2024)
by: Shao, Yijia, et al.
Published: (2024)
Beyond Text: Unveiling Privacy Vulnerabilities in Multi-modal Retrieval-Augmented Generation
by: Zhang, Jiankun, et al.
Published: (2025)
by: Zhang, Jiankun, et al.
Published: (2025)
Privacy-Preserving Instructions for Aligning Large Language Models
by: Yu, Da, et al.
Published: (2024)
by: Yu, Da, et al.
Published: (2024)
How Privacy-Savvy Are Large Language Models? A Case Study on Compliance and Privacy Technical Review
by: Liu, Yang, et al.
Published: (2024)
by: Liu, Yang, et al.
Published: (2024)
Embedding-Informed Adaptive Retrieval-Augmented Generation of Large Language Models
by: Huang, Chengkai, et al.
Published: (2024)
by: Huang, Chengkai, et al.
Published: (2024)
Benchmarking Retrieval-Augmented Large Language Models in Biomedical NLP: Application, Robustness, and Self-Awareness
by: Li, Mingchen, et al.
Published: (2024)
by: Li, Mingchen, et al.
Published: (2024)
R4: Reinforced Retriever-Reorder-Responder for Retrieval-Augmented Large Language Models
by: Zhang, Taolin, et al.
Published: (2024)
by: Zhang, Taolin, et al.
Published: (2024)
A Survey on Retrieval-Augmented Text Generation for Large Language Models
by: Huang, Yizheng, et al.
Published: (2024)
by: Huang, Yizheng, et al.
Published: (2024)
RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language Models
by: Huang, Jie, et al.
Published: (2023)
by: Huang, Jie, et al.
Published: (2023)
Taxonomy-Guided Zero-Shot Recommendations with LLMs
by: Liang, Yueqing, et al.
Published: (2024)
by: Liang, Yueqing, et al.
Published: (2024)
Similar Items
-
Can Knowledge Editing Really Correct Hallucinations?
by: Huang, Baixiang, et al.
Published: (2024) -
Can Large Language Models Identify Authorship?
by: Huang, Baixiang, et al.
Published: (2024) -
Understanding and Mitigating Cross-lingual Privacy Leakage via Language-specific and Universal Privacy Neurons
by: Dong, Wenshuo, et al.
Published: (2025) -
Sanitize Your Responses: Mitigating Privacy Leakage in Large Language Models
by: Fu, Wenjie, et al.
Published: (2025) -
Do LLMs Know What Is Private Internally? Probing and Steering Contextual Privacy Norms in Large Language Model Representations
by: Wang, Haoran, et al.
Published: (2026)