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I counted something like 30 different instances of run-on exclamation marks ("!!!!!!!!!!!") and weird mannerisms ("Waitwaitwaitwait.") in just one GLM 5.3 Flash session. Our token budgets are getting eaten up by this stuff...

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I expect it's actually not wasted and there's meaning behind what seems like nonsense to us in helping it achieve it's goal. Which is mildly chilling but not unexpected.

I think this is a known phenomenon: even in non-reasoning models, adding useless/filler tokens before an answer improves task performance. The model is doing some computation during the filler. See: https://arxiv.org/html/2404.15758v1

It is. Processing tokens is the only time model has to do computation, and if you ask it a tough problem, there is some minimal amount of computation it needs to perform to process and solve it - pre-CoT in particular you could guarantee failure by forcing model to be concise, and thus giving it less computational budget than necessary to compute the answer.

(This is I think where people parroting out "stochastic parrot" are stuck even today - not realizing that "predicting next tokens" is hiding arbitrary computation underneath, with token stream acting as input and clock signal...)

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