HyperNet injects facts into frozen LLMs by generating LoRA weights
rohanpaul_ai · x · 2026-07-24
The post describes HyperNet, a hypernetwork that turns natural-language facts into LoRA weights for a frozen target model.
- The base model stays fully frozen.
- A separate network learns to convert incoming facts into LoRA adapters.
- Those adapters are applied during the forward pass to steer the model toward the injected knowledge.
- The method does not fine-tune the target LLM on the new facts.
The attached figure shows the architecture and highlights that only the hypernetwork parameters are trained while the target model remains unchanged. The paper is titled “Scaling Laws for Hypernetwork-Based Knowledge Injection in LLMs.”
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