Bypassing inference bottlenecks: Accelerating complex AI search with Retrieve-for-Train
The Retrieve-for-Train framework introduces a novel approach to AI search by leveraging reinforcement learning during training to bypass the computational overhead of inference-time reasoning. This method enables efficient, property-aligned query decomposition, improving both the quality and speed o











