LLMs when given code mixing languages will typically execute as if it worked anyway. I have a theory this is because correct examples are the majority on the we

LLMs when given code mixing languages will typically execute as if it worked anyway. I have a theory this is because correct examples are the majority on the web. Since LLMs don't have the data with the feedback all the humans have seen constructing these examples, there is no way it could understand. We need to feed LLMs these types of input/error loops explicitly to improve performance or reduce iterations in this area. Otherwise it'll be stuck making many small mistakes forever. Again, this is my theory.