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Found 3 papers, 2 papers with code
Safe-CLIP: Removing NSFW Concepts from Vision-and-Language Models
We show how this can be done by fine-tuning a CLIP model on synthetic data obtained from a large language model trained to convert between safe and unsafe sentences, and a text-to-image generator.
Multi-Class Explainable Unlearning for Image Classification via Weight Filtering
Machine Unlearning has recently been emerging as a paradigm for selectively removing the impact of training datapoints from a network.
Revisiting The Evaluation of Class Activation Mapping for Explainability: A Novel Metric and Experimental Analysis
As the request for deep learning solutions increases, the need for explainability is even more fundamental.
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