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arXiv · 2501.04424

NSA: Neuro-symbolic ARC Challenge

Paweł Batorski·Jannik Brinkmann·Paul Swoboda
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Abstract

The Abstraction and Reasoning Corpus (ARC) evaluates general reasoning capabilities that are difficult for both machine learning models and combinatorial search methods. We propose a neuro-symbolic approach that combines a transformer for proposal generation with combinatorial search using a domain-specific language. The transformer narrows the search space by proposing promising search directions, which allows the combinatorial search to find the actual solution in short time. We pre-train the trainsformer with synthetically generated data. During test-time we generate additional task-specific training tasks and fine-tune our model. Our results surpass comparable state of the art on the ARC evaluation set by 27% and compare favourably on the ARC train set. We make our code and dataset publicly available at https://github.com/Batorskq/NSA.

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Paweł Batorski, Jannik Brinkmann, Paul Swoboda. 2025-01-08. NSA: Neuro-symbolic ARC Challenge. https://doi.org/10.14428/esann%2F2026.es2026-119

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