Oct. 7, 2022, 1:17 a.m. | Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala, Christopher Ré

cs.CL updates on arXiv.org arxiv.org

Large language models (LLMs) transfer well to new tasks out-of-the-box simply
given a natural language prompt that demonstrates how to perform the task and
no additional training. Prompting is a brittle process wherein small
modifications to the prompt can cause large variations in the model
predictions, and therefore significant effort is dedicated towards designing a
painstakingly "perfect prompt" for a task. To mitigate the high degree of
effort involved in prompt-design, we instead ask whether producing multiple
effective, yet imperfect, …

arxiv language language models strategy

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