Unverified50% confidenceFactExact time
ARC (Abstraction and Reasoning Corpus) is a general intelligence benchmark proposed by François Chollet in 2019, consisting of visual grid puzzles that require inducing transformation rules from examples and applying them to new inputs.
1
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50%
Confidence
Long-term
Relevance
10/28/2026
First Seen
Sources
Harness Engineering: The Secret to Tripling the Same Model's Score
youtubeThe Agentic Enterprise10/28/2026
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UnverifiedARC-AGI基准由Keras创始人François Chollet于2019年提出，每道题都是独一无二的视觉图案变换任务，用于衡量抽象推理能力而非模式匹配79% similarUnverifiedINKBOT 会生成一份可检视的「视觉简报」（Visual Brief），展示需求来源、约束条件和各要素之间的关系59% similarUnverifiedArc's design has a steep learning curve; mechanisms such as sidebar interaction, the spaces concept and automatic archiving are unfriendly to Chrome users.59% similarUnverifiedThe authors developed an interactive visual analytics system for identifying models at a macro level and drilling down to specific discriminative tokens and code context.58% similarUnverifiedThe current mainstream approach to agent memory is to embed everything and retrieve by similarity, which answers 'what looks like this query', not 'what the agent needs next'.58% similar
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