Before revision: A semantic parsing model is crucial to natural language processing applications such as goal-oriented dialogue systems .
After revision: Currently used semantic parsing systems deployed in voice assistants can require weeks to train. Datasets for these models often receive small and frequent updates, data patches. Each patch requires training a new model. To reduce training time, one can fine-tune the previously trained model on each patch, but naive fine-tuning exhibits catastrophic URLetting - degradation of the model performance on the data not represented in the data patch .