That sounds very similar to what we know in self-supervised learning as representation collapse. I wonder if we could copy some of the anti-collapse mechanisms from SSL into GPT... after all, they are ways to increment the differential entropy. However, I'm not sure if it could be useful after all: any pure function cannot produce more entropy than the entropy it receives... and natural language as text has much less entropy than other domains... [edit: typos]