{"url":"/dataset/arc-the-abstraction-and-reasoning-corpus","name":"ARC (The Abstraction and Reasoning Corpus)","full_name":null,"description_markdown":"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.","description_withheld":null,"homepage":"https://github.com/fchollet/ARC","introduced_date":"2019-11-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-measure-of-intelligence","title":"On the Measure of Intelligence","first_author":"François Chollet","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["ARC (The Abstraction and Reasoning Corpus)"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}