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I think we agree that LLMs learn from seeing chess games. I don't agree that LLMs aren't modeling chess at all - there seems to be no evidence for this. A thinking trace of a chess game with an LLM would certainly show the LLM trying to think about possible moves and evaluating their trade offs, even in the absence of a game board that it uses to keep state. I'm sure they are more likely to make mistakes if they aren't keeping track of the board, but so are humans.
To be honest, I'm not sure what kind of evidence would change your mind here if existing thinking traces are not enough. Anthropic researchers found that models are doing complex modeling for tasks as simple as deciding when to start a new line when writing text. Looking into a model to really understand how it's modeling something as complicated as a chess game would require a research budget.
Edit: there was a dude who trained a small model on next token prediction and found that it maintains a board state internally. So I guess now we can put this to bed?
Sure, in the sense that good human players can beat LLMs at chess. That said, the best models play at a class C level and do significantly better than the average chess.com player, which I think is hard to explain away by appealing to the models having memorized a bunch of openings.
The fact that they (allegedly) regularly make illegal moves is evidence of it.
One thing that would change my mind is if LLMs regularly and accurately solved problems which require modeling. For example, the (fresh) carwash puzzle.
It really depends on the model. Some of them don't make illegal moves, or at least do so rarely.
Certainly if LLMs started (verifiably) playing perfect chess in the sense of never making illegal moves, I would accept as evidence that they are creating chess models.
If an LLM made illegal moves only rarely, I'm not sure what I'd make of it.
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