V. Sharan

Learning cannot be simplified to proper learning, as some multiclass problems resist embedding in any properly learnable class, defying conventional wisdom.

Despite architectural differences, language models exhibit convergent evolution by learning similar periodic features for number representation, but achieving geometric separability depends on subtle training factors.