November 17, 2023 Uncategorized Leave a comment

Skeleton-of-Thought: Parallel decoding speeds up and improves LLM output

A figure showing the difference between the normal sequential decoding approach and the Skeleton-of-Thought approach. Given a question, the left part of the figure shows that the normal sequential decoding approach generates the answer sequentially from the beginning to the end. The right part of the figure shows that the Skeleton-of-Thought approach first prompts the LLM to give a skeleton of answer and then expand multiple points in the skeleton in parallel to get the final answer.

Large language models (LLMs) such as LLaMA and OpenAI’s GPT-4 are revolutionizing technology. However, one

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