Knowing What to Solve Before How: Preplan Empowered LLM Mathematical Reasoning
Current plan-based reasoning methods improve large language models (LLMs) by inserting a planning stage before execution, giving rise to the question $\rightarrow$ plan $\rightarrow$ cot paradigm. While effective, a closer examination reveals an inherent paradigm-level gap: both the planning and its execution stages decide how to solve a problem, while the prior question of what to solve; recognizing the problem type, the applicable tools, and the foreseeable pitfalls; remains entirely implicit. To bridge this gap, we propose PPC (Preplan-Plan-CoT), a framework that introduces an explicit problem-understanding stage, the preplan, yielding a new question $\rightarrow$ preplan $\rightarrow$...
| Authors | Shaojie Wang, Liang Zhang |
|---|---|
| Primary category | cs.CL |
| Published | 28 May 2026 |
| Last updated at source | 28 May 2026 |
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