I find that available LLMs have difficulty recalling instances in specific works by given authors. For example, if you ask GPT-4 "In which Philip K. Dick novel does the protagonist character consider converting to Judaism and moving to Israel?" it will respond with Dick's best known book _The Man in the High Castle_ and the character Frank Fink. The answer is incorrect. Israel does not exist in the world of that novel; furthermore, the character of Fink already is Jewish. The correct answer is Angel Archer in _The Transmigration of Timothy Archer_.
I have considered the feasibility of fine-tuning an LLM on the writings of a specific author. The idea is that it could aid writing in this way: If I currently am researching a specific author across multiple of their books, I often will get a quote of theirs trapped in my head some length of time after reading it. If I have neglected to jot down (or even to highlight) the source of the quote, I could ask the model where the remembered passage came from and get back a higher-quality response.
I have considered the feasibility of fine-tuning an LLM on the writings of a specific author. The idea is that it could aid writing in this way: If I currently am researching a specific author across multiple of their books, I often will get a quote of theirs trapped in my head some length of time after reading it. If I have neglected to jot down (or even to highlight) the source of the quote, I could ask the model where the remembered passage came from and get back a higher-quality response.