Time-Causal Model

A computational model that enforces temporal coherence in predictions by ensuring that the sequence of recognized events follows a logical causal order. In recipe tracking, a time-causal model prevents the system from predicting that an earlier step is currently happening after a later step has been confirmed complete, filtering out duplicate or out-of-order predictions. This approach is particularly important for cooking where visually similar actions may occur at different stages and previously processed ingredients may remain in the camera's field of view.