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Do language models have beliefs about the world? Dennett (1995) famously argues that even thermostats have beliefs, on the view that a belief is simply an informational state decoupled from any motivational state.
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Earlier work this paper cites.
Do animals have beliefs?
Daniel Dennett. 1995 · 1995
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