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> Speculative decoding is not really worthwhile for sparsely-loaded models.

If wonder if you can train a model to optimize this, by trying to make the expert selection sticky across a few tokens, without too much quality loss.

Another fun idea might be to try to build a model where the router chooses the expert 1-3 tokens in advance.

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> If wonder if you can train a model to optimize this, by trying to make the expert selection sticky across a few tokens

You can!

> AFM 3 Core Advanced makes routing decisions per prompt. A lightweight, dense block selects a fixed set of experts during initial processing, periodically reselecting them during generation.

https://machinelearning.apple.com/research/introducing-third...

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