I think therein lies another fun benchmark to show that LLM don't generalize: ask the llm to solve the same logic riddle, only in different languages. If it can solve it in some languages, but not in others, it's a strong argument for just straightforward memorization and next token prediction vs true generalization capabilities.
I would expect that the "classics" have all been thoroughly discussed on the Internet in all major languages by now. But if you could re-train a model from scratch and control its input, there are probably many theories you could test about the model's ability to connect bits of insight together.