> LLM-as-a-Judge

Empirically, many problems look like they're easier to check than they are to solve. This seems like a reasonable way to bootstrap a little extra performance, with prior art in well-known DeepMind experiments. It's unclear if it works recursively (I imagine not), but the core idea is solid.

I’m not reacting to the idea of using an LLM as a judge in general. That’s a proven path.

I’m specifically reacting to using it to reward the chain of thought during RL training because models love to hack their rewards, learning any possible shortcut rather than the task we want them to.