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LLMs 在科学怀疑论面前表现各异，新研究发现

作者 PulseAugur 编辑部 · [2 个来源] ·

一篇新的 arXiv 论文研究了大型语言模型（LLMs）如何应对科学怀疑论，特别是在气候变化、疫苗和进化论等有争议的领域。该研究测试了三个开源指令微调模型：Llama-3.1-8B、Qwen2.5-7B 和 Mistral-7B。与对谄媚退缩的担忧相反，这些模型表现出不同的行为：Llama-3.1-8B 表现出反应性断言，Qwen2.5-7B 表现出表面上的犹豫，而 Mistral-7B 则表现为不回应。研究发现，这种鲁棒性并非总是可靠的，尤其是在疫苗等安全关键领域，在怀疑论的压力下可能会减弱。 AI

影响 揭示了 LLM 对怀疑论的鲁棒性是复杂且依赖于领域的，突显了在关键领域潜在的安全风险。

排序理由 发布在 arXiv 上的研究论文，详细介绍了 LLM 的行为。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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LLMs 在科学怀疑论面前表现各异，新研究发现

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发布在 arXiv 上的研究论文，详细介绍了 LLM 的行为。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Minjong Cheon ·

    因错误原因而稳健：LLM 对科学怀疑论稳健性的表征几何学

    arXiv:2607.01951v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly consulted on contested scientific questions, raising the concern that they will sycophantically retreat from established consensus when a user signals doubt -- drifting toward a false …

  2. arXiv cs.CL TIER_1 English(EN) · Minjong Cheon ·

    错误原因的鲁棒性：LLM 对科学怀疑论鲁棒性的表征几何学

    Large language models (LLMs) are increasingly consulted on contested scientific questions, raising the concern that they will sycophantically retreat from established consensus when a user signals doubt -- drifting toward a false balance that treats settled science as one view am…

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