Techniques intended to reduce or remove the influence of specific data from a trained model without full retraining. Approaches and effectiveness vary; some providers offer deletion workflows or re-training processes, but the scope of guarantees, documentation, and verification methods differs across implementations.
See: Algorithmic Disgorgement (Model Deletion); Guardrails; Right to be Forgotten