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Consistency Without Alignment: Item-Sensitive Language Models Indistinguishable From Random

Huynh, Cris
arXiv (All) · Papers
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artificial-intelligencecomputation-and-language
Item-sensitivity, defined as whether a model's choice depends on the specific input rather than on its own output prior, is widely reported as evidence of task competence. We show this evidence is necessary but not sufficient using a forced-choice signalling task abstracted from the board game Decep
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