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View original post on X: ARC PrizeOfficial
Published
27/100

ARC-AGI score curves link v1 and v2 results across models

AIARC Prize says ARC-AGI-2 scores follow a power curve, v2 = v1^4.53, that explains about 98% of the variation in scores. Models tied on ARC-AGI-1 can still differ by over 20 percentage points on ARC-AGI-2.
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Plotting ARC-AGI model scores reveals a strong relationship across all three benchmarks.

For example, the power curve v2 = v1^4.53 explains about 98% of the variation in ARC-AGI-2 scores. Models tied on ARC-AGI-1 can still differ by over 20 percentage points on ARC-AGI-2.

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ARC Prize · x.comPublished · added here

Original title: Plotting ARC-AGI model scores reveals a strong relationship across all three benchmarks.

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ReasoningEvals & benchmarks