B) Has learning though "self-play" (like with AlphaZero etc) been demonstrated working for improving LLMs? What is the latest key research on this?
It might be a constraint on the evolution of godlike intelligence, or AGI. But at that point we're so far out in bong-hit territory that it will be impossible to say who's right or wrong about what's coming.
Has learning though "self-play" (like with AlphaZero etc) been demonstrated working for improving LLMs?
My understanding (which might be incorrect) is that this amounts to RLHF without the HF part, and is basically how DeepSeek-R1 was trained. I recall reading about OpenAI being butthurt^H^H^H^H^H^H^H^H concerned that their API might have been abused by the Chinese to train their own model.
R1 managed to replicate a model on the level of one one they had access to. But as far as I know they did not improve on its predictive performance? They did improve in inference time, but that is another thing. The ability to replicate a model is well demonstrated and quite common practice for some years already, see teacher-student distillation.