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State of Privacy-Preserving AI | Report | ScienceToStartup
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Privacy-Preserving AI
State of Privacy-Preserving AI
12 papers · avg viability 6.3
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Top papers
Anonymous-by-Construction: An LLM-Driven Framework for Privacy-Preserving Text
(8.0)
Knowledge Priors for Identity-Disentangled Open-Set Privacy-Preserving Video FER
(7.0)
SEAL-Tag: Self-Tag Evidence Aggregation with Probabilistic Circuits for PII-Safe Retrieval-Augmented Generation
(7.0)
Towards Privacy-Preserving Federated Learning using Hybrid Homomorphic Encryption
(7.0)
Nonparametric Variational Differential Privacy via Embedding Parameter Clipping
(7.0)
Not All Entities are Created Equal: A Dynamic Anonymization Framework for Privacy-Preserving Retrieval-Augmented Generation
(7.0)
Only Whats Necessary: Pareto Optimal Data Minimization for Privacy Preserving Video Anomaly Detection
(7.0)
StegaFFD: Privacy-Preserving Face Forgery Detection via Fine-Grained Steganographic Domain Lifting
(5.0)
Hidden Elo: Private Matchmaking through Encrypted Rating Systems
(5.0)
MPU: Towards Secure and Privacy-Preserving Knowledge Unlearning for Large Language Models
(5.0)
PrivHAR-Bench: A Graduated Privacy Benchmark Dataset for Video-Based Action Recognition
(5.0)
Lightweight, Practical Encrypted Face Recognition with GPU Support
(4.0)
SoK: Practical Aspects of Releasing Differentially Private Graphs
(4.0)
