Learning to Repair: Repairing model output errors after deployment using a dynamic memory of feedback

Niket Tandon, Aman Madaan, Peter Clark +1

Large language models (LMs), while powerful, are not immune to mistakes, but can be difficult to retrain. Our goal is for an LM to continue to improve after deployment, without ret…