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You obviously can do that though; diffusion models produce better (fsvo better) images the more steps you run of them.

Similarly, LLMs can produce better answers if you teach them thinking strategies that remind them to put the available evidence and intermediate steps in their context window. Otherwise they'll tend to hallucinate an answer out of vaguely correct words.



Diffusion models are a different architecture, namely, a recursive or iterative one. Transformer models are not recursive or iterative.


Sure they are. It only natively outputs one token; the recursive process is how you get the rest out of them.


You’re totally right … should’ve thought that one through more.




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