Datasets › ARC (The Abstraction and Reasoning Corpus)
ARC (The Abstraction and Reasoning Corpus)
The Abstraction and Reasoning Corpus (ARC) is a dataset created by François Chollet in 2019. It’s designed to measure the gap between machine and human learning. The dataset consists of 1000 image-based reasoning tasks. Each task provides an input image and asks for an output image. The goal is to solve these tasks using a system that can understand and learn abstract concepts, and apply reasoning skills to generate the correct output. This dataset poses a significant challenge for AI systems and is used to advance research in artificial intelligence and machine learning.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
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License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
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Languages archive 2025-07-28
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Variants archive 2025-07-28
- ARC (The Abstraction and Reasoning Corpus)
1 variant name, as the archive lists them.
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