Why reward models are still key to understanding alignment

In an era dominated by direct preference optimization and LLMasajudge, why do we still need a model to output only a scalar reward?
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Source code: https://github.com/natolambert/interconnects-tools
Original post: In an era dominated by direct preference optimization and LLM-as-a-judge, why do we still need a model to output only a scalar reward?

Podcast figures:
Figure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reward-models/img_004.png
Figure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reward-models/img_009.png

0:00 Why reward models are still key to understanding alignment

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