Co-occurring keywords · papers mentioning both
Papers
Venom: Liquid Diffusion-Guided Gradient Inversion for Breaking Differential Privacy in Federated Learning
AAAI 2026
A New Federated Learning Framework Against Gradient Inversion Attacks
AAAI 2025
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
AISTATS 2025
EmByte: Decomposition and Compression Learning for Small yet Private NLP
EMNLP 2025
Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning
ICCV 2025
Gradient Inversion Attack in Federated Learning: Exposing Text Data through Discrete Optimization
COLING 2025
Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning
CVPR 2025
GRAIN: Exact Graph Reconstruction from Gradients
ICLR 2025
How to Recover Long Audio Sequences Through Gradient Inversion Attack With Dynamic Segment-based Reconstruction
Interspeech 2025
MMGIA: Gradient Inversion Attack Against Multimodal Federated Learning via Intermodal Correlation
IJCAI 2025
Concealing Sensitive Samples against Gradient Leakage in Federated Learning
AAAI 2024
DAGER: Exact Gradient Inversion for Large Language Models
NeurIPS 2024
Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective
AAAI 2024
High-Fidelity Gradient Inversion in Distributed Learning
AAAI 2024
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning
CVPR 2024
Maximum Knowledge Orthogonality Reconstruction With Gradients in Federated Learning
WACV 2024
Mixing Gradients in Neural Networks as a Strategy To Enhance Privacy in Federated Learning
WACV 2024
Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks
AAAI 2024
Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients
EMNLP 2024
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks
ICLR 2024
Breaching FedMD: Image Recovery via Paired-Logits Inversion Attack
CVPR 2023
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis
ICML 2023
Dropout Is NOT All You Need to Prevent Gradient Leakage
AAAI 2023
Enhancing Privacy Preservation in Federated Learning via Learning Rate Perturbation
ICCV 2023
Instance-wise Batch Label Restoration via Gradients in Federated Learning
ICLR 2023