You can train a LLM to inverse summarised thinking into thinking text. It’s not perfect, but it gets you maybe 80% of the quality with proper techniques.

Paper: https://arxiv.org/abs/2603.07267

FWIW, there’s not that much value protected here anyway IMHO, and even raw thinking text can lie (as shown by Anthropic’s amazing research), so for legitimate interpretability research it’s limited.

Scaling frontier performance hasn’t been SFT-bounded for a while now; it’s now basically how much you can scale RL rollouts.