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Privacy

2794 directly classified papers

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Papers

Direct Unlearning Optimization for Robust and Safe Text-to-Image Models NIPS 2024
Certified private data release for sparse Lipschitz functions AISTATS 2024
A Comparative Analysis of Federated Learning for Speech-Based Cognitive Decline Detection INTERSPEECH 2024
Differentially Private Reward Estimation with Preference Feedback AISTATS 2024
Scalable DP-SGD: Shuffling vs. Poisson Subsampling NIPS 2024
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients AISTATS 2024
MICo: Preventative Detoxification of Large Language Models through Inhibition Control NAACL 2024
Privacy-Preserving Decentralized Actor-Critic for Cooperative Multi-Agent Reinforcement Learning AISTATS 2024
Privacy PORCUPINE: Anonymization of Speaker Attributes Using Occurrence Normalization for Space-Filling Vector Quantization INTERSPEECH 2024
Differentially Private Set Representations NIPS 2024
Where Am I From? Identifying Origin of LLM-generated Content EMNLP 2024
Noise-Aware Differentially Private Regression via Meta-Learning NIPS 2024
Demystifying Verbatim Memorization in Large Language Models EMNLP 2024
Fine-grained Pluggable Gradient Ascent for Knowledge Unlearning in Language Models EMNLP 2024
Instance-Optimal Private Density Estimation in the Wasserstein Distance NIPS 2024
Unlocking Memorization in Large Language Models with Dynamic Soft Prompting EMNLP 2024
PostMark: A Robust Blackbox Watermark for Large Language Models EMNLP 2024
Invariant Aggregator for Defending against Federated Backdoor Attacks AISTATS 2024
GS-Hider: Hiding Messages into 3D Gaussian Splatting NIPS 2024
Generated Distributions Are All You Need for Membership Inference Attacks Against Generative Models WACV 2024
ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods EMNLP 2024
Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion EMNLP 2024
Unlocking the Potential of Large Language Models for Clinical Text Anonymization: A Comparative Study ACL 2024
Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning EMNLP 2024
Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts EMNLP 2024