Towards Better Statistical Understanding of Watermarking LLMs
Fuente:
arXiv
Saved in:
| Main Authors: | Cai, Zhongze, Liu, Shang, Wang, Hanzhao, Zhong, Huaiyang, Li, Xiaocheng |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards Optimal Statistical Watermarking
by: Huang, Baihe, et al.
Published: (2023)
by: Huang, Baihe, et al.
Published: (2023)
Distributional Information Embedding: A Framework for Multi-bit Watermarking
by: He, Haiyun, et al.
Published: (2025)
by: He, Haiyun, et al.
Published: (2025)
Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach
by: He, Haiyun, et al.
Published: (2024)
by: He, Haiyun, et al.
Published: (2024)
TATTOOED: A Robust Deep Neural Network Watermarking Scheme based on Spread-Spectrum Channel Coding
by: Pagnotta, Giulio, et al.
Published: (2022)
by: Pagnotta, Giulio, et al.
Published: (2022)
Better and Simpler Lower Bounds for Differentially Private Statistical Estimation
by: Narayanan, Shyam
Published: (2023)
by: Narayanan, Shyam
Published: (2023)
Diffusion-aided Task-oriented Semantic Communications with Model Inversion Attack
by: Wang, Xuesong, et al.
Published: (2025)
by: Wang, Xuesong, et al.
Published: (2025)
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy
by: Jin, Richeng, et al.
Published: (2023)
by: Jin, Richeng, et al.
Published: (2023)
Towards Watermarking of Open-Source LLMs
by: Gloaguen, Thibaud, et al.
Published: (2025)
by: Gloaguen, Thibaud, et al.
Published: (2025)
Universal Exact Compression of Differentially Private Mechanisms
by: Liu, Yanxiao, et al.
Published: (2024)
by: Liu, Yanxiao, et al.
Published: (2024)
Explainable Semantic Federated Learning Enabled Industrial Edge Network for Fire Surveillance
by: Dong, Li, et al.
Published: (2024)
by: Dong, Li, et al.
Published: (2024)
Enabling Deep Learning-based Physical-layer Secret Key Generation for FDD-OFDM Systems in Multi-Environments
by: Zhang, Xinwei, et al.
Published: (2022)
by: Zhang, Xinwei, et al.
Published: (2022)
Watermarking Recommender Systems
by: Zhang, Sixiao, et al.
Published: (2024)
by: Zhang, Sixiao, et al.
Published: (2024)
Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
by: Huang, Alyssa, et al.
Published: (2023)
by: Huang, Alyssa, et al.
Published: (2023)
Spectrum Breathing: Protecting Over-the-Air Federated Learning Against Interference
by: Wang, Zhanwei, et al.
Published: (2023)
by: Wang, Zhanwei, et al.
Published: (2023)
Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy
by: Xie, Songjie, et al.
Published: (2024)
by: Xie, Songjie, et al.
Published: (2024)
DRGW: Learning Disentangled Representations for Robust Graph Watermarking
by: Li, Jiasen, et al.
Published: (2026)
by: Li, Jiasen, et al.
Published: (2026)
Robustness Implies Privacy in Statistical Estimation
by: Hopkins, Samuel B., et al.
Published: (2022)
by: Hopkins, Samuel B., et al.
Published: (2022)
Differentially Private Fair Binary Classifications
by: Ghoukasian, Hrad, et al.
Published: (2024)
by: Ghoukasian, Hrad, et al.
Published: (2024)
Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation
by: Vithana, Sajani, et al.
Published: (2024)
by: Vithana, Sajani, et al.
Published: (2024)
CorBin-FL: A Differentially Private Federated Learning Mechanism using Common Randomness
by: Salehi, Hojat Allah, et al.
Published: (2024)
by: Salehi, Hojat Allah, et al.
Published: (2024)
An Efficient Difference-of-Convex Solver for Privacy Funnel
by: Huang, Teng-Hui, et al.
Published: (2024)
by: Huang, Teng-Hui, et al.
Published: (2024)
In-Application Defense Against Evasive Web Scans through Behavioral Analysis
by: Ousat, Behzad, et al.
Published: (2024)
by: Ousat, Behzad, et al.
Published: (2024)
Collaborative Inference over Wireless Channels with Feature Differential Privacy
by: Seif, Mohamed, et al.
Published: (2024)
by: Seif, Mohamed, et al.
Published: (2024)
Modular Neural Wiretap Codes for Fading Channels
by: Seifert, Daniel, et al.
Published: (2024)
by: Seifert, Daniel, et al.
Published: (2024)
Machine Learning Predictors for Min-Entropy Estimation
by: Blanco-Romero, Javier, et al.
Published: (2024)
by: Blanco-Romero, Javier, et al.
Published: (2024)
Inference Privacy: Properties and Mechanisms
by: Tian, Fengwei, et al.
Published: (2024)
by: Tian, Fengwei, et al.
Published: (2024)
On Homomorphic Encryption Based Strategies for Class Imbalance in Federated Learning
by: Guleria, Arpit, et al.
Published: (2024)
by: Guleria, Arpit, et al.
Published: (2024)
Adversary-Aware Private Inference over Wireless Channels
by: Seif, Mohamed, et al.
Published: (2025)
by: Seif, Mohamed, et al.
Published: (2025)
Optimal Guarantees for Auditing Rényi Differentially Private Machine Learning
by: Kim, Benjamin D., et al.
Published: (2026)
by: Kim, Benjamin D., et al.
Published: (2026)
STAMP: Selective Task-Aware Mechanism for Text Privacy
by: Tian, Fengwei, et al.
Published: (2026)
by: Tian, Fengwei, et al.
Published: (2026)
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity
by: Pour, Alireza F., et al.
Published: (2023)
by: Pour, Alireza F., et al.
Published: (2023)
The importance of feature preprocessing for differentially private linear optimization
by: Sun, Ziteng, et al.
Published: (2023)
by: Sun, Ziteng, et al.
Published: (2023)
Rao Differential Privacy
by: Soto, Carlos
Published: (2025)
by: Soto, Carlos
Published: (2025)
GeoClip: Geometry-Aware Clipping for Differentially Private SGD
by: Gilani, Atefeh, et al.
Published: (2025)
by: Gilani, Atefeh, et al.
Published: (2025)
Comparing privacy notions for protection against reconstruction attacks in machine learning
by: Biswas, Sayan, et al.
Published: (2025)
by: Biswas, Sayan, et al.
Published: (2025)
FedNC: A Secure and Efficient Federated Learning Method with Network Coding
by: Shi, Yuchen, et al.
Published: (2023)
by: Shi, Yuchen, et al.
Published: (2023)
Local Differential Privacy with Correlated Noise Achieves Central-DP Optimal Cost
by: Pathegama, Madhura, et al.
Published: (2026)
by: Pathegama, Madhura, et al.
Published: (2026)
ScionFL: Efficient and Robust Secure Quantized Aggregation
by: Ben-Itzhak, Yaniv, et al.
Published: (2022)
by: Ben-Itzhak, Yaniv, et al.
Published: (2022)
Privacy Against Agnostic Inference Attacks in Vertical Federated Learning
by: Varasteh, Morteza
Published: (2023)
by: Varasteh, Morteza
Published: (2023)
Vicious Classifiers: Assessing Inference-time Data Reconstruction Risk in Edge Computing
by: Malekzadeh, Mohammad, et al.
Published: (2022)
by: Malekzadeh, Mohammad, et al.
Published: (2022)
Similar Items
-
Towards Optimal Statistical Watermarking
by: Huang, Baihe, et al.
Published: (2023) -
Distributional Information Embedding: A Framework for Multi-bit Watermarking
by: He, Haiyun, et al.
Published: (2025) -
Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach
by: He, Haiyun, et al.
Published: (2024) -
TATTOOED: A Robust Deep Neural Network Watermarking Scheme based on Spread-Spectrum Channel Coding
by: Pagnotta, Giulio, et al.
Published: (2022) -
Better and Simpler Lower Bounds for Differentially Private Statistical Estimation
by: Narayanan, Shyam
Published: (2023)