I'm not sure it's likely that the LLM here learned from gcc. The size optimization work here is focused on learning phase orderings for LLVM passes/the LLVM pipeline, which wouldn't be at all applicable to gcc.
Additionally, they train approximately half on assembly and half on LLVM-IR. They don't talk much about how they generate the dataset other than that they generated it from the CodeLlama dataset, but I would guess they compile as much code as they can into LLVM-IR and then just lower that into assembly, leaving gcc out of the loop completely for the vast majority of the compiler specific training.
Additionally, they train approximately half on assembly and half on LLVM-IR. They don't talk much about how they generate the dataset other than that they generated it from the CodeLlama dataset, but I would guess they compile as much code as they can into LLVM-IR and then just lower that into assembly, leaving gcc out of the loop completely for the vast majority of the compiler specific training.