The result is mildly interesting - improvement on an isolated task but none on the full benchmark - but what would be much more compelling is curiosity-driven replay in an LLM context combined with chain- or tree-of-thought techniques. This would be the machine analogy to noticing your confusion, a sort of "what do I need to know" or "what am I overlooking"? Anecdotally, language models perform better when you prompt them to ask their own questions in the process of answering yours, so I would expect curiosity to have a meaningful impact.