Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models — HN submission

Fri, 02 Aug 2024 03:40:53 GMT

Ask HN: Research Papers on Prompt Engineering?

Since prompting is such an important topic, I'm looking for a list of papers on how to improve prompts (around a year old, but preferably less). So far, I've found two: - "Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models" (https://arxiv.org/pdf/2305.04091v3) - "Accessing GPT-4 Level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B: A Technical Report" (https://arxiv.org/pdf/2406.07394v2) Do you recommend any other papers?

1 point; 2 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models — mentioned by fragsworth

Thu, 18 May 2023 21:47:08 GMT

> furthermore there planning abilities are non-existent. Have you even tried to ask it to plan things out? It can plan things out. In fact, just asking it to plan things out has shown significant benchmark improvements for general questions: https://arxiv.org/pdf/2305.04091.pdf

Paper and discussion history. A mention is not an endorsement.

Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models · HackerPapers discussions

Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models — HN submission

Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models — mentioned by fragsworth