The depth of recursion becomes a tunable compute axis at inference time, requiring no retraining. A small model, by reading itself, can iterate toward answers that neither it nor any of its workers could reach in a single pass.
文章描述了一种递归推理机制，称小模型通过自我迭代可以达到单次推理无法达到的结果，但未提供具体的性能提升数据或实验证据。这一断言缺乏量化依据，需要更多实验数据支持。