Researchers introduced Conditional Optimal Bridge for Riemannian Activation Steering (Cobras), a method for controlling large language models at inference time. Cobras casts activation steering as a Schrödinger Bridge on the residual-stream hypersphere, providing a principled derivation of the log-density-ratio steering objective. This approach yields a query-adaptive steering field and a support score for out-of-distribution interventions. Cobras outperforms prior steering methods in various model-task settings, maintaining or improving out-of-distribution performance. The method is available on GitHub.