Imagen de Portada

Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wang, Xun, Xu, Jing, Boenisch, Franziska, Backes, Michael, Choquette-Choo, Christopher A., Dziedzic, Adam
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Localizing Memorization in SSL Vision Encoders
por: Wang, Wenhao, et al.
Publicado: (2024)

ADAGE: Active Defenses Against GNN Extraction
por: Xu, Jing, et al.
Publicado: (2025)

DP-GPL: Differentially Private Graph Prompt Learning
por: Xu, Jing, et al.
Publicado: (2025)

Memorization in Graph Neural Networks
por: Jamadandi, Adarsh, et al.
Publicado: (2025)

Localizing and Mitigating Memorization in Image Autoregressive Models
por: Kasliwal, Aditya, et al.
Publicado: (2025)

Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives
por: Hanke, Vincent, et al.
Publicado: (2024)

Privacy Attacks on Image AutoRegressive Models
por: Kowalczuk, Antoni, et al.
Publicado: (2025)

Differentially Private Prototypes for Imbalanced Transfer Learning
por: Wahdany, Dariush, et al.
Publicado: (2024)

Have it your way: Individualized Privacy Assignment for DP-SGD
por: Boenisch, Franziska, et al.
Publicado: (2023)

Captured by Captions: On Memorization and its Mitigation in CLIP Models
por: Wang, Wenhao, et al.
Publicado: (2025)

On the Privacy Risk of In-context Learning
por: Duan, Haonan, et al.
Publicado: (2024)

Memorization in Self-Supervised Learning Improves Downstream Generalization
por: Wang, Wenhao, et al.
Publicado: (2024)

Curation Leaks: Membership Inference Attacks against Data Curation for Machine Learning
por: Wahdany, Dariush, et al.
Publicado: (2026)

Differentially Private Federated Learning With Time-Adaptive Privacy Spending
por: Kiani, Shahrzad, et al.
Publicado: (2025)

Unlocking Post-hoc Dataset Inference with Synthetic Data
por: Zhao, Bihe, et al.
Publicado: (2025)

CDI: Copyrighted Data Identification in Diffusion Models
por: Dubiński, Jan, et al.
Publicado: (2024)

Implementing Adaptations for Vision AutoRegressive Model
por: Shaikh, Kaif, et al.
Publicado: (2025)

Radioactive Watermarks in Diffusion and Autoregressive Image Generative Models
por: Meintz, Michel, et al.
Publicado: (2025)

Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks
por: Podhajski, Marcin, et al.
Publicado: (2024)

Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models
por: Hintersdorf, Dominik, et al.
Publicado: (2024)

Privacy Amplification for Matrix Mechanisms
por: Choquette-Choo, Christopher A., et al.
Publicado: (2023)

On Stealing Graph Neural Network Models
por: Podhajski, Marcin, et al.
Publicado: (2025)

MUC: Machine Unlearning for Contrastive Learning with Black-box Evaluation
por: Wang, Yihan, et al.
Publicado: (2024)

Finding DoRI: Discovery of Retained Images in Diffusion Models
por: Kowalczuk, Antoni, et al.
Publicado: (2025)

Adversarial Attacks and Defenses on Graph-aware Large Language Models (LLMs)
por: Olatunji, Iyiola E., et al.
Publicado: (2025)

Privacy Auditing of Large Language Models
por: Panda, Ashwinee, et al.
Publicado: (2025)

Personalized Differential Privacy for Ridge Regression
por: Acharya, Krishna, et al.
Publicado: (2024)

Optimal Rates for $O(1)$-Smooth DP-SCO with a Single Epoch and Large Batches
por: Choquette-Choo, Christopher A., et al.
Publicado: (2024)

SecP-Tuning: Efficient Privacy-Preserving Prompt Tuning for Large Language Models via MPC
por: Luo, Jinglong, et al.
Publicado: (2025)

Teach LLMs to Phish: Stealing Private Information from Language Models
por: Panda, Ashwinee, et al.
Publicado: (2024)

Privacy Side Channels in Machine Learning Systems
por: Debenedetti, Edoardo, et al.
Publicado: (2023)

Exploring the limits of strong membership inference attacks on large language models
por: Hayes, Jamie, et al.
Publicado: (2025)

Augment then Smooth: Reconciling Differential Privacy with Certified Robustness
por: Wu, Jiapeng, et al.
Publicado: (2023)

SOS! Soft Prompt Attack Against Open-Source Large Language Models
por: Yang, Ziqing, et al.
Publicado: (2024)

Beautiful Images, Toxic Words: Understanding and Addressing Offensive Text in Generated Images
por: Kumar, Aditya, et al.
Publicado: (2025)

User Inference Attacks on Large Language Models
por: Kandpal, Nikhil, et al.
Publicado: (2023)

Leveraging Soft Prompts for Privacy Attacks in Federated Prompt Tuning
por: Nguyen, Quan Minh, et al.
Publicado: (2026)

EmojiPrompt: Generative Prompt Obfuscation for Privacy-Preserving Communication with Cloud-based LLMs
por: Lin, Sam, et al.
Publicado: (2024)

Controlled privacy leakage propagation throughout overlapping grouped learning
por: Kiani, Shahrzad, et al.
Publicado: (2025)

Regulation Games for Trustworthy Machine Learning
por: Yaghini, Mohammad, et al.
Publicado: (2024)