I wouldn't be surprised if Chinese had no irregularities in the tense system – it's a very isolating language. But here's one irregularity: the negation of 有 is 没有 ("to not have/possess"), but the simple negation of every other verb is 不 + verb. You can negate other verbs with 没, but then it's implied to be 没有 + verb, which makes the verb into something like a present participle. E.g., 没吃 = "to have not eaten".
"How are we counting Chinese versus non-Chinese papers? Because often, it seems to be just doing it via, "Is their last name Chinese?" Which seems like it really is going to miscount." seems unreasonably skeptical. It's not too much harder to just look up the country of the university/organization that published the paper.
I'm not sure what the source is for the statement that "China publishes more papers on deep learning than the US", but in their 2018 Report, AI Index describes their country affiliation methodology as such: "An author’s country affiliation is determined based on his or her primary organization, which is provided by authors of the papers. Global organizations will use the headquarters’ country affiliation as a default, unless the author is specific in his/her organization description. For example, an author who inputs “Google” as their organization will be affiliated with the United States, one that inputs “Google Zurich” will be affiliated with Europe. Papers are double counted when authors from multiple geographies collaborate. For example, a paper with authors at Harvard and Oxford will be counted once for the U.S. and once for Europe."
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