least-to-most prompting

**Least-to-most prompting** is the **reasoning method that decomposes a difficult problem into simpler subproblems solved in progressive order** - each intermediate result becomes context for the next step. **What Is Least-to-most prompting?** - **Definition**: Prompting strategy that first breaks a task into easier components, then solves them sequentially. - **Reasoning Structure**: Moves from foundational sub-questions to final synthesis. - **Task Fit**: Effective for compositional reasoning and multi-stage logic problems. - **Prompt Design**: Requires clear decomposition instructions and controlled intermediate output format. **Why Least-to-most prompting Matters** - **Complexity Control**: Reduces cognitive load by turning one hard task into manageable steps. - **Error Localization**: Easier to identify and correct where reasoning deviates. - **Reliability Improvement**: Structured progression can reduce shortcut and jump-to-answer errors. - **Compositional Generalization**: Helps on tasks requiring ordered dependency handling. - **Tool Compatibility**: Substeps can be routed to specialized tools or models. **How It Is Used in Practice** - **Decomposition Stage**: Generate explicit subtask list with dependency ordering. - **Sequential Solving**: Solve each subtask and feed verified outputs forward. - **Final Integration**: Produce final answer from accumulated sub-results with consistency checks. Least-to-most prompting is **a practical decomposition-first reasoning strategy** - progressive subproblem solving improves control and accuracy on tasks that are hard to solve in a single inference step.