4 ms·
One confounding factor here is the proliferation of autocorrect and grammar “advisors” in popular apps like gmail etc. One algorithm tweak could change a lot of
by refibrillator 2y ago
One confounding factor here is the proliferation of autocorrect and grammar “advisors” in popular apps like gmail etc. One algorithm tweak could change a lot of writing at that scale.
While the word frequency stats are damning, there doesn’t seem to be any evidence presented that directly ties the changes to LLMs specifically.
- daemonologist 2y agoI think they address this to some degree by checking different year pairings (end of page 2), where the only excess usage they found was of words related to current events (ebola, coronavirus, etc.) and even then not to the same degree as the 2022-24 pair. It would be interesting to analyze how well a language model is able to predict each abstract. In theory if the text was largely written by a model then a similar model might be able to predict it more accurately than it would a human-written abstract. (Of course the variety of models and frequency at which they're updated makes this more difficult.)
- deleted 2y ago[deleted]