#memorization

Researchers reveal a new method using latent vector fields to understand how neural autoencoders balance memorization and generalization, enhancing interpretability without modifying models.

Meta and collaborators developed a novel framework to accurately quantify how much language models memorize training data, estimating GPT models store around 3.6 bits per parameter and providing new insights into memorization versus generalization.