LARC is a dataset built from ARC (Abstraction and Reasoning Corpus). ARC is a set of tasks that tests an agent's ability to flexibly solve novel problems. While most ARC tasks are easy for humans, they are challenging for state-of-the-art AI.
LARC or Language-annotated ARC, is a collection of natural language descriptions by a group of human participants, unfamiliar both with ARC and with each other, who instruct each other on how to solve ARC tasks. LARC contains successful instructions for 88% of the ARC tasks.
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