I don't think they're quibbling over semantics but providing constructive cautionary feedback. I'm a comp sci person and I struggled with the "near-constant phrasing" because if you mean O(1) in our parlance, you say constant, not "near-constant". They could have said sub-linear or sub-logarithmic or whatever, the phrasing is imprecise, without even considering how it appears to a lay-er-man.

Also I'm not a huge fan of defending jargon for the sake of it. Sometimes there are efficiency gains, sure. But the paper here is quite approachable generally speaking. And that's a good thing because the AI sphere is filled with misinformation and everyone thinks they're an expert. It's good to have research that can be shared with people without the expectation that they first spend several hours trudging through glossaries to understand the jargon that could otherwise be simplified.