The GPT-4 versus 3.5 win rate is only like two to one ratio. It's great if models do more per-kit ones, but it's bad if you get to a stage where a human can't look at it and be like, okay, this is good or bad. Break tasks into smaller tasks really helps with the evaluation. Alyssa uses language models to say, oh, this paper found this result, this paper studied these types of people, this paper had these limitations. And then all you have to evaluate is kind of the answer and like a small chunk of text,. which is way more manageable.

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