Paraphrasing can also be used for inference-time evaluations: by paraphrasing each paragraph that the model generates, we scrub away encoded information before it can be used—but seeing a scratchpad that looks nothing like the scratchpads the model is used to may be very distracting to the model, and make it perform worse even if it is not using encoded reasoning. In some exploratory experiment, this sort of paraphrasing seemed to be distracting for the model: just asking the model to break up its thoughts into <thought></thought> blocks without doing any paraphrasing was enough to make pass@1 MATH accuracy drop by 7%.
But I’d welcome experiments about this, maybe there are ways to do chunking which are less distracting than the thing I tried! (These experiments are somewhat easy to do with just API access.)
In one of the footnotes, I say
But I’d welcome experiments about this, maybe there are ways to do chunking which are less distracting than the thing I tried! (These experiments are somewhat easy to do with just API access.)