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Recursive depth in masked diffusion models can dramatically enhance parameter efficiency, enabling models to perform as well as much larger counterparts without the added computational burden.
Despite the buzz around Tiny Recursive Models, directly adapting their refinement mechanism into autoregressive architectures yields no reliable performance boost, suggesting the original TRM's success may stem from other factors.
