Comment by IAmNotACellist

I'm struggling to understand what he's talking about. Starting with "passing up," did he invent this terminology? The only input you have to an LLM is the prompt, which gets tokenized. And if you were to send DCFG rules or a compiled version of it as part of the request, how would that fundamentally alter the way that the tokens are predicted? If the model predicts something that doesn't conform to the grammar you require, is he proposing re-prompting until it gets it right?