Unverified50% confidenceFactExact time
ARC-AGI is a general intelligence benchmark proposed by François Chollet, comprising a series of colored grid transformation tasks that require a model to infer abstract transformation rules from very few examples and apply them to new inputs.
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10/14/2026
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UnverifiedThe original version of ARC-AGI is characterized by abstract visual grid puzzles, where given input-output examples, the model is required to induce the hidden transformation rules.77% similarVerifiedARC-AGI由AI研究者François Chollet设计，用于创造对人类直觉简单但对依赖数据记忆的语言模型极为困难的测试集77% similarVerifiedThe ARC-AGI benchmark was proposed by François Chollet in 2019 to evaluate AI's abstract reasoning and generalization capabilities when faced with entirely novel problems.76% similarUnverifiedChollet has repeatedly emphasized that ARC is merely a tool for measuring a certain type of abstract reasoning ability rather than the ultimate criterion for determining AGI, and that achieving a high score on ARC-AGI does not equate to achieving artificial general intelligence.75% similarUnverifiedARC-AGI-3 is a reasoning capability benchmark designed by François Chollet that tests AI's ability to generalize reasoning to task rules it has never seen before, specifically designed to resist brute-force memorization.73% similar
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