Foresight: planning future perception in streaming VLMs without retraining

Streaming VLMs can dynamically configure computational pathways to match evolving scene dynamics without retraining. By leveraging inherent anticipation capabilities, the method plans future perception requirements concurrently with inference to adjust processing levels based on predicted visual events. This allows for adaptive computation with negligible overhead during continuous stream processing.