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RLHF is not a tax on capability: preference tuning also raises maths and code scores, which is why the labs keep reaching for it.

Drawn from what Nathan Lambert said

What this subject means

reinforcement learning Training by reward: environments, verifiable tasks, value functions, and whether it works or merely beats what came before.

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What Nathan Lambert actually said

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  1. Nathan Lambert

    Research scientist at the Allen Institute for AI

    And the important thing to say is that no matter how you want the model to behave, these RLHF and preference-tuning techniques also improve performance. So, on things like math evals and code evals, there is something innate to these, what is called contrastive loss functions.

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