Label Embedding Refresh

Automatischer Uebersetzungsentwurf (German) for "Label Embedding Refresh": Label Embedding Refresh is a ml index workflow that updates vector representations after source data changes for ground-truth or weak-supervision annotation. It uses batch jobs, backfills, and index validation so teams can keep retrieval results current while keeping evidence, reliability, and public-safe operational boundaries clear.

“Beispielentwurf: The machine learning team used Label Embedding Refresh when the label set had disagreement, so the team could keep retrieval results current before the model moved into evaluation.”