Comment by mrweasel
5 days ago
Someone apparently did observe ChatGPT (I think it was ChatGPT) switch to Chinese for some parts of it's reasoning/calculations and then back to English for the final answer. That's somehow even weirder than the LLM giving different answers depending on the input.
Reminds me of this funny video: https://www.youtube.com/watch?v=NY3yWXWjYjA ("You know something has gone wrong when he switches to Chinese")
I've seen this happen as well with o3-mini, but I'm honestly not sure what triggered it. I use it all the time but have only had it switch to Chinese during reasoning maybe twice.
I've seen Grok sprinkle random Chinese characters into responses I asked for in ancient Greek and Latin.
I get strange languages sprinkled through my Gemini responses, including some very obscure ones. It just randomly changes language for one or two words.
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Isn't it just it getting increasingly incoherent as non-English data fraction increases?
Last I checked, none of open weight LLMs has languages other than English as its sole dominant language represented in the dataset.
I saw Claude 3.7 write a comment in my code in Russian followed by, likely from a previous modification, the English text “Russian coding” for no reason.
> the LLM giving different answers depending on the input.
LLMs are actually designed to have some randomness in their responses.
To make the answer reproducible, set the temperature to O (eliminating randomness) and provide a static seed (ensuring consistent results) in the LLM's configuration.
The influence of the (pseudo-)random number generator is called "temperature" in most models.
Setting it to 0 in theory eliminates all randomness, and instead of choosing one from a list of next words that may be predicted, always only the MOST PROBABLY word would be chosen.
However, in practice, setting the temperature to 0 in most GUIs does not actually set the temperature to 0, but to a "very small" value ("epsilon"), the reason being to avoid a division by zero exception/crawsh in a mathematical formula. So don't be surprised if you cannot get rid of random behavior entirely.
> the reason being to avoid a division by zero exception/crawsh in a mathematical formula
Why don't they just special-case it?
It's not necessary in most inference engines I've seen to set the temperature to 0—the randomness in the temperature is drawn from the seed, so a static seed will work for any temperature.
In had it doing the reasoning in Turkish and English despite the question being in German.
i’ve seen that with deepseek