“大型语言模型中‘忠实推理’的可证伪拓扑特征”
我们已预注册了一种可测试的协议，用于检测大型语言模型（LLMs）中的几何一致性推理。该协议预测在元认知状态下，Betti数、Kolmogorov-Smirnov（KS）熵和脆弱性在消融实验中会增加。欢迎进行复制研究。
<p>OSF协议: https://osf.io/2r6v8
预印本和案例研究: https://doi.org/10.5281/zenodo/18346699<p>这不是哲学——这是一个可证伪的数学假设。如果你有GPU访问权限和拓扑数据分析（TDA）/深度学习（DL）专业知识，你可以在一个周末内验证它。
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We've pre-registered a testable protocol for detecting geometrically consistent reasoning in LLMs. Predicts increased Betti numbers, KS entropy, and fragility under ablation during meta-cognitive states. Open for replication.<p>OSF Protocol: https://osf.io/2r6v8
Preprint & case studies: https://doi.org/10.5281/zenodo/18346699<p>This isn't philosophy — it's a falsifiable math hypothesis. If you have GPU access and TDA/DL expertise, you can verify it in a weekend.