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Yes, there is a degeneration of replies, the longer a conversation goes. Maybe this student kind of hit the jackpot by triggering a fiction writer reply inside the dataset. It is reproducible in a similar way as the student did, by asking many questions and at a certain point you'll notice that even simple facts get wrong. I personally have observed this with chatgpt multiple times. It's easier to trigger by using multiple similar but non related questions, as if the AI tries to push the wider context and chat history into the same LLM training "paths" but burns them out, blocks them that way and then tries to find a different direction, similar to the path electricity from a lightning strike can take.
I wonder if it’s related to training on website comments, which often role the same trajectory.