# Least-to-Most Prompting

> Least-to-most prompting first asks the model to break a complex problem into simpler subproblems, then solves them in order, feeding each answer into the next.

- Identifier: PTL-0030
- Category: Reasoning Elicitation
- Canonical URL: https://protologue.com/t/least-to-most-prompting/
- Also known as: problem decomposition
- Introduced: 2022

## Description

Zhou et al. showed it generalizes to problems harder than those in the examples, a weakness of standard chain-of-thought, with strong results on compositional generalization benchmarks.

## Related terms

- [Chain-of-Thought Prompting](https://protologue.com/t/chain-of-thought/)
- [Plan-and-Solve Prompting](https://protologue.com/t/plan-and-solve-prompting/)
- [Self-Ask](https://protologue.com/t/self-ask/)
- [Prompt Chaining](https://protologue.com/t/prompt-chaining/)

## Sources

- Zhou et al. (2022). Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. https://arxiv.org/abs/2205.10625

## Cite this entry

Protologue. (2026). Least-to-Most Prompting. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0030). https://protologue.com/t/least-to-most-prompting/

License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)