Unrelated to the paper, which is about asking LLM's to figure out which parts of a document were removed, but my assumption has been that to an LLM there is nothing "missing" in the sense that any input leads to valid computation and output.

For example, I asked ChatGPT to explain something I typed randomly

>It looks like you've entered “dosfi8q3anfdfiqr”, which appears to be a random string or perhaps a typo—it's not a recognized acronym, code, or term in any common context I’m aware of. Could you share a bit more about where you found this?

Although the answer is correct, my point is that anything you give to the LLM is going to be put under some bucket. The LLM can't say "I don't know what that is." Instead it says "that is a random string." As far as the LLM is concerned, it knows every possible input and concept that anyone could ever type into it, it's just that its "understanding" of what that means (after the tokens have gone through the neural network) doesn't necessarily match what any human being thinks it means.