Bypassing inference bottlenecks: Accelerating complex AI search with Retrieve-for-Train

Google Research presents Retrieve-for-Train, an ICML 2026 paper proposing a reinforcement learning framework to compile query fan-out strategies. The method distills optimized exploration into a lightweight diffusion retriever, aiming to reduce inference-time reasoning costs for complex search tasks. No usable model weights or API are currently available for developers to integrate.