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Manipulating Chess-GPT’s World Model | Adam Karvonen

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Manipulating Chess-GPT’s World Model

Manipulating Chess-GPT’s World Model Note: This work has since been turned into a paper accepted to the Conference on Language Modeling , but the average reader will probably prefer the blog post. In my previous post I introduced Chess-GPT, a language model I trained to predict the next character in a game of chess given a PGN string (1.e4 e5 2.Nf3 …). Through the process of training to output the next character, it learns to compute the state of the chess board and to estimate the skill level of the players in the game given an arbitrary PGN string as input. I demonstrated this using linear p

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