[r/ML] [D] Has interpretability research been applied to model training?

Summary

A recent discussion highlights how attention probes, a tool from interpretability research, can reduce token costs by enabling early exits in Chain-of-Thought models. This prompts a question about whether such interpretability techniques have been systematically applied during model training, including pre-training, SFT, or RL. The user is exploring if these methods could improve the models themselves, beyond just inference efficiency.

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