1. It uses non-idiomatic terminology in several places.

2. It repeats the same finding over and over (141 flops per byte, for example), without going deeper.

3. I stopped reading about a quarter of the way through because it felt like it was never going to stop teasing me about what it was going to tell me and actually tell me it.

4. It seems to assume the reader has a lot of context that isn't explicitly laid out (and which the reader wouldn't get just from reading the prior work, which is cited).

For example, I understand some of what it is saying because I used some similar techniques to benchmark things in the past (running at multiple scales to estimate overhead + marginal gains with a linear regression), but I wouldn't expect anyone who hasn't personally done that to follow the prose.

> 4. It seems to assume the reader has a lot of context that isn't explicitly laid out (and which the reader wouldn't get just from reading the prior work, which is cited

I've had this complaint well before LLMs were used. People writing about topics they have a lot of knowledge in the subject tend to make the assumption only other subject knowledgeable readers will read it. Or that it never edited by a real editor that would enforce rules like spelling out acronyms on first use. Or forcing additional information when too many details have been left out on the assumption it would already be known.

There's plenty of this type of writing to have trained the bots that way