It is possible that these similarities were caused by other models being fine-tuned or primed on R1 thinking traces, before reinforcement learning.

Repository here: github.com/cpldcpu/llmb...

That is a very neat idea to extend the latent states available for "reasoning". It feels a bit unnatural to force the models to output text for reasoning steps, even if some intermediate concepts can maybe not be easily expressed in written language.