Adaptive Instructed-Retriever: Frontier-Quality Search at 2x Lower Latency

Databricks unveiled Adaptive Instructed-Retriever, a retrieval model that dynamically switches between parallel and sequential search to cut latency by half while keeping accuracy on par with leading models. The blog details a fixed step limit, early‑stop logic, and benchmark gains, but does not publish full weight files or integration code.