Scaling Laws for Train-Time Knowledge Injection via Hypernetworks

This research explores using hypernetworks to generate fixed LoRA adapters for large-scale factual knowledge injection during training. The method decouples the hypernetwork's injection capacity from the target model size, providing a scalable alternative to standard fine-tuning.