ARC-AGI-2: Why the New Benchmark Is Even Harder
AI Summary
Chollet announces ARC-AGI-2, a harder successor benchmark designed after the top 2024 ARC Prize winner achieved 55.5% using hybrid neurosymbolic approaches. The new benchmark introduces more compositional reasoning tasks, longer chains of inference, and fewer visual shortcuts. ARC-AGI-2 targets the 40-50% gap that even the best 2024 systems couldn't cross, aiming to distinguish genuine compositional reasoning from the pattern-matching strategies that allowed top-performing 2024 submissions to score over 50%. Human baseline on ARC-AGI-2 remains above 80%.
Original excerpt
After the top 2024 solution hit 55.5%, Chollet raises the bar. ARC-AGI-2 targets the reasoning gap that remains between current best systems and human-level performance.
Key design principle: remove any path to high scores that doesn't require genuine compositional reasoning. The previous benchmark allowed some pattern-matching shortcuts; ARC-AGI-2 closes them.
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Chollet announces ARC-AGI-2, a harder successor benchmark designed after the top 2024 ARC Prize winner achieved 55.5% using hybrid neurosymbolic approaches. The new benchmark introduces more compositional reasoning tasks, longer chains of inference, and fewer visual shortcuts. ARC-AGI-2 targets the…
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"ARC-AGI-2: Why the New Benchmark Is Even Harder" was written by François Chollet. It is curated in the François Chollet vault on Burn 451, which covers agi evaluation & arc-agi.
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