GLM 5.3 flash seems to get more excited the longer it has been trying to hunt down a problem. Complete with caps, many exclamation marks and emoji.
It is funny sometimes because the actual issue it traced down was mostly inconsequential.
GLM 5.3 flash seems to get more excited the longer it has been trying to hunt down a problem. Complete with caps, many exclamation marks and emoji.
It is funny sometimes because the actual issue it traced down was mostly inconsequential.
OMG I think I found a way to center a div!!!
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...
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