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Prompt engineering for text generation: Difference between revisions
Prompt engineering for text generation (view source)
Revision as of 23:09, 5 April 2023
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==Self-Consistency Sampling== | ==Self-Consistency Sampling== | ||
Self-consistency sampling is a method for generating multiple outputs using a [[temperature]] greater than 0 and selecting the best candidate from the generated outputs. The criteria for choosing the best candidate may vary according to the task. A common approach is to use [[majority vote]]. In tasks that are easy to validate, such as programming questions with unit tests, the outputs can be run through an interpreter and their correctness can be verified using unit tests. | [[Self-consistency sampling]] is a method for generating multiple outputs using a [[temperature]] greater than 0 and selecting the best candidate from the generated outputs. The criteria for choosing the best candidate may vary according to the task. A common approach is to use [[majority vote]]. In tasks that are easy to validate, such as programming questions with unit tests, the outputs can be run through an interpreter and their correctness can be verified using unit tests.<ref name="”118”">Wang et al. (2022a) Self-Consistency Improves Chain of Thought Reasoning in Language Models https://arxiv.org/abs/2203.11171</ref> | ||
==Chain of Thought Prompting== | ==Chain of Thought Prompting== | ||