Can you actually “unlearn” a document from a trained mo...

While gradient-based unlearning is an active research area, it lacks the guarantees of avoiding the data during the initial training. Operationally, you should maintain modular checkpoints linked to data provenance, enabling the reconstruction of the corpus without the disputed content for a fresh training run. For already deployed models, implement output filters to suppress verbatim reproduction of the claimed content as a stopgap measure while the expensive retraining process is completed.