HyperThink Amortizes LLM Reasoning via Text-to-Parameter Hypernetworks

HyperThink uses a lightweight hypernetwork to predict parameter updates for a base LLM, replacing slow sequential reasoning traces with a single query-conditioned update. A vector-quantized decoder constrains these updates to reusable patterns, enabling concise step-by-step generation without high inference-time overhead.