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Found 4 papers, 3 papers with code
Towards Safer Large Language Models through Machine Unlearning
To address this gap, we introduce Selective Knowledge negation Unlearning (SKU), a novel unlearning framework for LLMs, designed to eliminate harmful knowledge while preserving utility on normal prompts.
Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning
Exploring the full spectrum of trade-offs between privacy, model utility, and runtime efficiency is critical for practical unlearning scenarios.
EEG4Students: An Experimental Design for EEG Data Collection and Machine Learning Analysis
However, during the COVID-19 pandemic, data collection and analysis could be more challenging.
Time Majority Voting, a PC-based EEG Classifier for Non-expert Users
Using Machine Learning and Deep Learning to predict cognitive tasks from electroencephalography (EEG) signals is a rapidly advancing field in Brain-Computer Interfaces (BCI).
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