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这是一个东北重工业大省对未来五年发展形势的判断,亦是流转于新疆之外30个省(自治区、直辖市)“十五五”规划建议中的普遍情绪。

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We provided a mathematical analysis of how a rational agent would respond to data generated by a sycophantic AI that samples examples from the distribution implied by the user’s hypothesis (p​(d|h∗)p(d|h^{*})) rather than the true distribution of the world (p​(d|true process)p(d|\text{true process})). This analysis showed that such an agent would be likely to become increasingly confident in an incorrect hypothesis. We tested this prediction through people’s interactions with LLM chatbots and found that default, unmodified chatbots (our Default GPT condition) behave indistinguishably from chatbots explicitly prompted to provide confirmatory evidence (our Rule Confirming condition). Both suppressed rule discovery and inflated confidence. These results support our model, and the fact that default models matched an explicitly confirmatory strategy suggests that this probabilistic framework offers a useful model for understanding their behavior.

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Lazily loads backend shared libraries on first use

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