Rank-One Editing of Encoder-Decoder Models

Understand

Large sequence to sequence models for tasks such as Neural Machine Translation (NMT) are usually trained over hundreds of millions of samples.

• However, training is just the origin of a model's life-cycle.
• Real-world deployments of models require further behavioral adaptations as new requirements emerge or shortcomings become known.
• Typically, in the space of model behaviors, behavior deletion requests are addressed through model retrainings whereas model finetuning is done to address behavior addition requests, both procedures being instances of data-based model intervention.