This September 18 2025 paper introduces a research project that applies **Schoenfeld’s Episode Theory**, a classic cognitive framework for analyzing human mathematical problem-solving, to understand the reasoning processes of **Large Reasoning Models (LRMs)**. The authors created a novel, publicly available benchmark by annotating thousands of sentences and paragraphs from model-generated solutions to math problems, using seven cognitive labels such as **Plan, Implement, and Verify**. This approach offers a **theoretically grounded methodology** for interpreting LRM cognition, demonstrating that machine reasoning exhibits structured, episodic patterns similar to human behavior. The resulting annotated corpus and analytical protocol aim to enable the development of more **transparent and controllable reasoning systems**.

Source:

https://arxiv.org/pdf/2509.14662