How would you tell that it's LLM-generated in that case?
If the submitter is prepared to explain the code and vouch for its quality then that might reasonably fall under "don't ask, don't tell".
However, if LLM output is either (a) uncopyrightable or (b) considered a derivative work of the source that was used to train the model, then you have a legal problem. And the legal system does care about invisible "bit colour".
It's (c) copyright of the operator.
For one simple reason. Intention.
Here's some code for example: https://i.imgur.com/dp0QHBp.png
Both sides written by an LLM. Both sides written based on my explicit prompts explaining exactly how I want it to behave, then testing, retesting, and generally doing all the normal software eng due diligence necessary for basic QA. Sometimes the prompts are explicitly "change this variable name" and it ends up changing 2 lines of code no different from a find/replace.
Also I'm watching it reason in real time by running terminal commands to probe runtime data and extrapolate the right code. I've already seen it fix basic bugs because an RFC wasn't adhered to perfectly. Even leaving a nice comment explaining why we're ignoring the RFC in that one spot.
Eventually these arguments are kinda exhausting. People will use it to build stuff and the stuff they build ends up retraining it so we're already hundreds of generations deep on the retraining already and talking about licenses at this point feels absurd to me.
I think you need to read the report from the US Copyright office that specifically says that it's *not* (c) copyright of the operator.
It doesn't matter if the "change this variable name" instruction ends up with the same result as a human operator using a text editor.
There is a big difference between "change this variable name" and "refactor this code base to extract a singleton".