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English(EN) Despite not being trained to, it turns out the Pearson correlation between a models AA Intelligence Index score and its ability to generate Base64 encoded responses is 0.91

新基准显示Base64生成能力与AI智能之间存在强关联

作者 PulseAugur 编辑部 · [1 个来源] ·

一项名为Encode Bench的新基准测试揭示了语言模型生成Base64编码响应的能力与其智能得分之间存在强相关性。该基准测试在需要解决问题、精确答案保留和正确编码的任务上对模型进行测试，发现与AA智能指数的皮尔逊相关性为0.91。虽然这可能表明了一种粗略的多步可靠性衡量方法，但创建者警告说，这并不能证明因果关系，可能反映了分词器行为或推理限制等其他因素。 AI

影响 该基准测试可能提供了一种新颖但粗略的方法来评估LLM的能力，超越了传统指标。

排序理由 该条目描述了一项新基准测试及其关于LLM能力的发现，属于研究范畴。[lever_c_demoted from research: ic=1 ai=1.0]

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新基准显示Base64生成能力与AI智能之间存在强关联

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该条目描述了一项新基准测试及其关于LLM能力的发现，属于研究范畴。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Valuable-Repeat-7347 ·

    尽管未经训练，但事实证明，模型AA Intelligence Index得分与其生成Base64编码响应的能力之间的皮尔逊相关系数为0.91

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1v3dpsk/despite_not_being_trained_to_it_turns_out_the/"> <img alt="Despite not being trained to, it turns out the Pearson correlation between a models AA Intelligence Index score and its ability to generate Ba…

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