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RLVR's success in long-horizon reasoning hinges on a smooth difficulty spectrum, where mastering easier sub-problems unlocks the ability to tackle harder ones, avoiding frustrating grokking plateaus.
Discrete diffusion models can now sample high-dimensional data with provable sublinear convergence rates, adapting to hidden structure without prior knowledge.
