[vidarh]

There's no value in an LLM doing arithmetic for the sake of doing arithmetic with the LLM. There's value in testing an LLMs ability to follow the rules for doing arithmetic that it already knows, because the ability to recognise that a problem matches a set of rules it already knows in part or whole and then applying those rules with precision is likely to generalise to overall far better problem solving abilities.

By all means, we should give LLMs lots and lots of specialised tools to let them take shortcuts, but that does not remove the reasons for understanding how to strengthen the reasoning abilities that would also make them good at maths.

EDIT: After having just coerced the current GPT4 to do arithmetic manually: It appears to have drastically improved in its ability to systematically following the required method, while ironically being far less willing to do so (it took multiple attempts before I got it to stop taking shortcuts that appeared to involve recognising this was a calculation it could use tooling to carry out, or ignoring my instructions to do it step by step and just doing it "in its head" the way a recalcitrant student might. It's been a while since I tested this, but this is definitely "new-ish".

[namibj]

Gaslighting LLMs does wonders. In this case, e.g., priming it by convincing it the tool is either inaccessible/overloaded/laggy, or here perhaps, telling it the python tool computed wrong and can thus not be trusted.