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This is pretty mind-boggling, to the point of suspecting an error in the methodology. If it is just a language model, then it has no baked in notion of test time tasks. How on earth does a language model know what is required of it at test-time without fine tuning? How does it know that the test time prompt are examples of the task, and not some story prompt it's supposed to riff off in random ways?

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Yes, mind-boggling.

For each task, the authors feed a context window of text with either zero to a few sample queries and responses, followed by a query without the response. The model generates a response for the last query. BTW, this approach is analogous to what you would do with a human being: you would provide zero to a few sample questions and answers, and then ask a question.

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