arXiv: cs.AI preprintsInternational5 November 2026
ConceptARC at Scale: Studying Conceptual Understanding in Reasoning Models
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arXiv:2611.06732v1 Announce Type: new Abstract: Large reasoning models (LRMs) perform well on challenging benchmarks, yet it remains unclear whether they form generalizable abstractions across conceptually related reasoning tasks. The Abstraction and Reasoning Corpus (ARC) provides a controlled testbed for studying abstraction, requiring solvers to infer transformation rules over two-dimensional grids from a small set of examples. While ARC evaluates rule abstraction within individual tasks, different tasks may share higher-level structure despite requiring different transformations$\unicode{x
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