Comment by schopra909
1 day ago
When it comes to reasoning specifically, it's a far simpler explanation IMO. Modern RLVR techniques like GRPO rely on the model understanding the likelihood of the generated phrase. This is really easy to compute for LLMs that are trained with next-word prediction. Diffusion models have a harder time accessing this likelihood value (i.e., you can approximate it but the approximation isn't good). Hence, reasoning doesn't work (yet) for diffusion models. Though, alternative approaches are currently being tried out in academia; so someone might crack it!
What is meant by "understanding" the likelihood?
Diffusion models, surely, are "trained with next-[pixel] prediction", and that should suffice, no?