Sure, but the value of logit matching is that it allows the smaller model to access richer representations that it has sufficient capacity to express but insufficient capacity to learn. In this case, we're not trying to distill the full capabilities of the large model. We just want to mimic instruction following, and we don't have any reason to believe the smaller model has insufficient capacity. So doesn't the lesson of knowledge distillation tell us that this should work just by matching low temperature logits (in other words, matching argmax only)? I don't see how this is fundamentally different from the standard knowledge distillation setting - it's just an easier instance of it