LLM-based surprisal is not interchangeable across models: different architectures compute word probabilities via visibly different internal computations, undermining representation-agnostic claims for Surprisal Theory.
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surprisal is Not a Theory
LLM-based surprisal is not interchangeable across models: different architectures compute word probabilities via visibly different internal computations, undermining representation-agnostic claims for Surprisal Theory.