Fine-tuning generative neural networks to improve few-shot performance

A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one more computers to perform operations for training a generative neural network, the operations comprising:

• obtaining a respective set of demonstration examples for each of a plurality of tasks, wherein each demonstration example comprises a respective example query and a respective example output for the respective example query;
• for each of the plurality of tasks:
• obtaining a training query for the task and a ground truth output for the training query for the task;
• determining, from the respective set of demonstration examples for the task, a subset of demonstration examples that are most similar to the training query;
• generating a training example for the generative neural network, wherein the training example comprises (i) a training input that includes the training query and the subset of demonstration examples that are most similar to the training query and (ii) the ground truth output for the training query for the task;
• and
• training the generative neural network on training data that includes the training examples for the plurality of tasks.

One or more non-transitory computer storage media storing instructions that when executed by one or more computers cause the one more computers to perform operations for training a generative neural network, the operations comprising:

• obtaining a respective set of demonstration examples for each of a plurality of tasks, wherein each demonstration example comprises a respective example query and a respective example output for the respective example query;
• for each of the plurality of tasks:
• obtaining a training query for the task and a ground truth output for the training query for the task;
• determining, from the respective set of demonstration examples for the task, a subset of demonstration examples that are most similar to the training query;
• generating a training example for the generative neural network, wherein the training example comprises (i) a training input that includes the training query and the subset of demonstration examples that are most similar to the training query and (ii) the ground truth output for the training query for the task;
• and
• training the generative neural network on training data that includes the training examples for the plurality of tasks.