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Least-to-Most Prompting(LtM)
Progressive problem decomposition from simple to complex components
In 30 seconds
- What
- Solves complex problems by first solving simpler versions, then progressively adding constraints or complexity to reach the full solution.
- When to use
- Multi-step problems where each step builds on prior results and simpler cases reveal patterns applicable to harder ones.
- Watch out
- Early mistakes in simple cases compound through all subsequent steps, making the final answer wrong despite correct later reasoning.
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Least-to-Most Prompting: Overview
Progressive problem decomposition from simple to complex components
- Hierarchical problem breakdown
- Bottom-up solution building
- Progressive complexity handling
- Builds on simpler solutions
- Reduces cognitive load
- Systematic approach to complex problems
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References
The papers, specifications, and repositories this pattern is based on.
- Least-to-Most Prompting Enables Complex Reasoning in Large Language Models (Zhou et al., 2022)arXiv:2205.10625
- Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (Wei et al., 2022)arXiv:2201.11903
- Decomposed Prompting: A Modular Approach for Solving Complex Tasks (Khot et al., 2022)arXiv:2210.02406
- Maieutic Prompting: Logically Consistent Reasoning (Jung et al., 2022)arXiv:2205.11822
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