2D Spatial Reasoning with Adaptive Neural Cellular Automata

The paper introduces Adaptive Neural Cellular Automata (aNCA), a new architecture that employs deformable convolutions to dynamically adjust its receptive field and iteratively reason over 2D spatial relationships in grid-like data such as images. aNCA is designed to address the limitations of current learning approaches in spatial reasoning tasks. Experiments on public benchmarks demonstrate state‑of‑the‑art performance and strong generalization on image‑based puzzles like Sudoku and maze shortest‑path problems.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

• benchmarks