Least-to-most prompting
Least-to-most prompting 籍由將大任務分細子任務，讓大型語言模型可以處理較複雜的大任務。使用Least-to-most prompting 包含兩個階段：
- Decomposition.
- The prompt in this stage contains constant examples that demonstrate the decomposition, followed by the specific question to be decomposed.
- Subproblem solving.
- The prompt in this stage consists of three parts:
- (1) constant examples demonstrating how subproblems are solved;
- (2) a potentially empty list of previously answered subquestions and generated solutions, and
- (3) the question to be answered next.
example
有一個小山坡，小明爬上去需要花4分鐘，爬下來需要花1分鐘。15分鐘內，小明可以爬上再爬下來回幾次？
- Decomposition
-
"有一個小山坡，小明爬上去需要花4分鐘，爬下來需要花1分鐘。15分鐘內，小明可以爬上再爬下來回幾次？" 該怎麼解決這個問題？
-
- Subproblem solving
- 包含子問題
-
"有一個小山坡，小明爬上去需要花4分鐘，爬下來需要花1分鐘。15分鐘內，小明可以爬上再爬下來回幾次？" Q: 爬上爬下一趙花多少時間？
-
- 將子問題的答案附上，再進一步提問
-
"有一個小山坡，小明爬上去需要花4分鐘，爬下來需要花1分鐘。15分鐘內，小明可以爬上再爬下來回幾次？" Q: 爬上爬下一趙花多少時間？ A : 爬上爬下一趟要花5分鐘 Q: 那麼15分鐘內可以爬上爬下來回幾次？
-
- 包含子問題
References
Zhou, D., Schärli, N., Hou, L., Wei, J., Scales, N., Wang, X., ... & Chi, E. (2022). Least-to-most prompting enables complex reasoning in large language models. arXiv preprint arXiv:2205.10625.