I fully agree with your final statement, but needing to constrain the problem in an artificial way to prove it's NP-complete doesn't mean the constraint was justified or realistic, because then you've only proved the constrained version of the decision problem is NP-hard.
There might be plenty of perfectly "good" tokenizers (whatever that ends up meaning) that can be found or generated without formulating their design as an NP-complete decision problem. Claiming "tokenization is NP-complete" (paper title) in general seems like an overstatement.
If it's NP-hard to even know whether the answer is bigger or smaller than a certain number, then it's obvious that in a non-formal way, finding the exact answer is at least as hard as NP-hard, whatever that means.
There might be plenty of perfectly "good" tokenizers (whatever that ends up meaning) that can be found or generated without formulating their design as an NP-complete decision problem. Claiming "tokenization is NP-complete" (paper title) in general seems like an overstatement.