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New benchmark shows strong link between Base64 generation and AI intelligence

By PulseAugur Editorial · [1 sources] ·

A new benchmark called Encode Bench has revealed a strong correlation between a language model's ability to generate Base64 encoded responses and its intelligence scores. The benchmark, which tests models on tasks requiring problem-solving, exact answer preservation, and correct encoding, found a Pearson correlation of 0.91 with the AA Intelligence Index. While this suggests a potential crude measure of multi-step reliability, the creator cautions that it does not prove causation and could reflect other factors like tokenizer behavior or reasoning limits. AI

IMPACT This benchmark may offer a novel, albeit crude, method for assessing LLM capabilities beyond traditional metrics.

RANK_REASON The item describes a new benchmark and its findings regarding LLM capabilities, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New benchmark shows strong link between Base64 generation and AI intelligence

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The item describes a new benchmark and its findings regarding LLM capabilities, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

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

    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

    <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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