Scaling Trust in Quantum Federated Learning: A Multi-Protocol Privacy Design
Authors: Dev Gurung, Shiva Raj Pokhrel | Published: 2025-12-03
Privacy Protection
Quantum Vanguard: Server Optimized Privacy Fortified Federated Intelligence for Future Vehicles
Authors: Dev Gurung, Shiva Raj Pokhrel | Published: 2025-12-02
Differentially Private In-Context Learning with Nearest Neighbor Search
Authors: Antti Koskela, Tejas Kulkarni, Laith Zumot | Published: 2025-11-06
Auditing M-LLMs for Privacy Risks: A Synthetic Benchmark and Evaluation Framework
Authors: Junhao Li, Jiahao Chen, Zhou Feng, Chunyi Zhou | Published: 2025-11-05
Design and Optimization of Cloud Native Homomorphic Encryption Workflows for Privacy-Preserving ML Inference
Authors: Tejaswini Bollikonda | Published: 2025-10-28
SPEAR++: Scaling Gradient Inversion via Sparsely-Used Dictionary Learning
Authors: Alexander Bakarsky, Dimitar I. Dimitrov, Maximilian Baader, Martin Vechev | Published: 2025-10-28
LLMs can hide text in other text of the same length
Authors: Antonio Norelli, Michael Bronstein | Published: 2025-10-22 | Updated: 2025-10-27
SimKey: A Semantically Aware Key Module for Watermarking Language Models
Authors: Shingo Kodama, Haya Diwan, Lucas Rosenblatt, R. Teal Witter, Niv Cohen | Published: 2025-10-11 | Updated: 2025-11-03
RepoMark: A Data-Usage Auditing Framework for Code Large Language Models
Authors: Wenjie Qu, Yuguang Zhou, Bo Wang, Yuexin Li, Lionel Z. Wang, Jinyuan Jia, Jiaheng Zhang | Published: 2025-08-29 | Updated: 2025-11-03
CryptPEFT: Efficient and Private Neural Network Inference via Parameter-Efficient Fine-Tuning
Authors: Saisai Xia, Wenhao Wang, Zihao Wang, Yuhui Zhang, Yier Jin, Dan Meng, Rui Hou | Published: 2025-08-17 | Updated: 2025-11-06