AI RESEARCH
ARC-AGI-2 Technical Report
arXiv CS.CL
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ArXi:2603.06590v1 Announce Type: new The Abstraction and Reasoning Corpus (ARC) is designed to assess generalization beyond pattern matching, requiring models to infer symbolic rules from very few examples. In this work, we present a transformer-based system that advances ARC performance by combining neural inference with structure-aware priors and online task adaptation. Our approach is built on four key ideas.