You say this is well-known, but my experience is talking chinese to the chinese LLM produces more efficient work, with less rambling in the thinking/reporting steps, and I have been presuming that it is because longer utf8-token still beats a bunch of utf7-compatible words for expressing the kinds of big ideas maths and code requires. 省字臃思

So I have to wonder why is token count so high in their examples? Here is my theory: I would not say 我遇见了一只大狗, but I would just say 遇大狗. I know I can't do that in English, but I think surely the researchers should know (or would ask someone?) how this works trying to compare phrases in isolation, so I wonder why is this test meaningful to them? Why are they doing that? Are they looking for this result? 字省思臊 I don't talk like google translate.

So who are these people and why are you listening to them and repeating what they say like it is so? Why exactly are you so convinced?