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Extracting Training Data from Large Language Models (Paper Explained)
USENIX Security '21 - Blind Backdoors in Deep Learning Models
USENIX Security '20 - High Accuracy and High Fidelity Extraction of Neural Networks
USENIX Security '24 - Making Them Ask and Answer: Jailbreaking Large Language Models in Few...
OSDI '26 - Revisiting Pipeline Parallelism for LLM Serving
USENIX Security '21 - Reducing Bias in Modeling Real-world Password Strength via Deep Learning...
USENIX Security '22 - Exploring the Security Boundary of Data Reconstruction via Neuron Exclusivity
USENIX Security '24 - Hijacking Attacks against Neural Network by Analyzing Training Data
USENIX Security '21 - Leakage of Dataset Properties in Multi-Party Machine Learning
USENIX Security '23 - PELICAN: Exploiting Backdoors of Naturally Trained Deep Learning Models In...
OSDI '26 - TrainMover: An Interruption-Resilient Runtime for ML Training
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Last Updated: September 14, 2026
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