The training data probably includes a lot more formal writing. As the major selling point of chatgpt is it sounding like it "knows" things. More "complex" verbiage is helpful to that. This type of writing is more common in things like textbooks and scientific writing in general which have been at least part of its training data.

LLMs, in fact, have slop profiles (aka overused tokens/phrases) common to the family/company, often from “inbreeding” by training on their own output.

Sometimes you can tell if new model “stole” output from another company this way. For instance, Deepseek R1 is suspiciously similar to Google Gemini, heh.

This longform writing benchmark tries to test/measure this (click the I on each model for infographics):

https://eqbench.com/creative_writing_longform.html

As well as some some disparate attempts on GitHub (actually all from the eqbench dev): https://github.com/sam-paech/slop-forensics

https://github.com/sam-paech/antislop-vllm

🤓☝️ akshually, crucial and essential are adjectives

Yeah, it's overly formal, but I do use each of those in regular conversion, just a lot more sparingly than AI seems to.