Like the N-closest algorithm, the weight of each candidate is given by the inverse of its distance to the input colour. Because of this, both algorithms produce output of a similar quality, although the N-convex method is measurably faster. As with the last algorithm, more details can be found in the original paper[2].
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Rank-3 factorization, shared-A tied-KV, RMSNorm, tied embed, curriculum learning
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