ARC Prize 2024: Technical Report
This addresses the problem of advancing towards AGI by improving generalization on novel tasks, though it is incremental as it builds on existing benchmark efforts.
The paper tackled the challenge of improving performance on the ARC-AGI benchmark, a key unsolved AI benchmark for measuring generalization, and reported that the state-of-the-art score increased from 33% to 55.5% through a global competition.
As of December 2024, the ARC-AGI benchmark is five years old and remains unbeaten. We believe it is currently the most important unsolved AI benchmark in the world because it seeks to measure generalization on novel tasks -- the essence of intelligence -- as opposed to skill at tasks that can be prepared for in advance. This year, we launched ARC Prize, a global competition to inspire new ideas and drive open progress towards AGI by reaching a target benchmark score of 85\%. As a result, the state-of-the-art score on the ARC-AGI private evaluation set increased from 33\% to 55.5\%, propelled by several frontier AGI reasoning techniques including deep learning-guided program synthesis and test-time training. In this paper, we survey top approaches, review new open-source implementations, discuss the limitations of the ARC-AGI-1 dataset, and share key insights gained from the competition.