First Scaling Laws for Hypernetwork Knowledge Injection Released With 39-Domain Dataset

Knowledge injection into frontier models — keeping LLMs factually current without full retraining — is a core unsolved problem at scale. This paper provides the first principled scaling curves for an alternative architecture, enabling model teams to predict hypernetwork design choices before training.