Instruction Inference from Input-Output Pairs
A key capability of Large Language Models is their ability to infer the underlying instruction for a task when provided with a series of input-output examples. By analyzing the relationship between the inputs and their corresponding outputs, the model can deduce the transformation rule or goal of the task.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Example of a Prompt Template for Generating Instructions from Input-Output Pairs
Instruction Inference from Input-Output Pairs
A developer wants a language model to generate a clear instruction for the task of 'summarizing a long paragraph into a single, concise sentence.' To do this, they will provide the model with a set of input-output examples and ask it to infer the instruction. Which of the following sets of examples is most likely to result in the desired instruction?
Diagnosing Issues in Instruction Inference
Crafting Examples for Instruction Inference
Learn After
A user wants a language model to infer the task of 'converting a list of names into a formal, alphabetized list, with each name prefixed by a title'. Which of the following sets of input-output examples would be most effective for the model to correctly deduce this specific, multi-step instruction?
Crafting Examples for Instruction Inference
Debugging Instruction Inference