The paper, and this comment, seem awfully reminiscent of creating a textbook of curated "maximally informative and distilled" set of cognitive examples to teach students with foundational learning a next level of reasoning.
The last few years of LLM progress have shown we can predict human "reasoning" responses to inputs by modeling likely human responses as if LLM generated. Put another way, most responses are not particularly reasoned, but chain of tokgen*.
Sit near someone who "talks to herself" while doing problems and it's even more evident.
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* tokgen definition: Listen to conversations in a cafeteria. Many are something other than thoughtful, responses that follow the prompts, with near perfect predictability. To differentiate from these responses and speech that comes after a pause and reflect, one can use the labels thought versus token generation or tokgen.