Grid Complexity Metrics Predict Solver Success on ARC-AGI Tasks
Researchers found that structural properties of intermediate grid states can predict whether symbolic solvers will successfully complete ARC-AGI tasks, with hand-crafted descriptors achieving 88.5% discrimination accuracy within tasks. The predictive signal is primarily driven by a single grid-complexity axis and generalizes across different solver architectures. This finding could enable early stopping strategies that reduce computational cost by 33-65% while maintaining solution success rates.
A new study on arXiv demonstrates that structural grid descriptors measured at 50% trajectory completion can reliably predict whether symbolic ARC-AGI solvers will succeed on individual tasks. Across 44,800 runs using two distinct solver architectures (beam search and Stochastic DFS) on 400 ARC tasks, hand-crafted features achieved mean within-task AUC of 0.885 (p < 0.001). The most predictive information concentrates along a single grid-complexity dimension, and this signal transfers across solver architectures with AUC 0.747-0.762. On a pre-registered held-out test set of 41 reliable tasks, the feature n_components_final achieved AUC 0.765 (95% CI [0.717, 0.810]). The predictive power is not explained by solver capacity differences and is only weakly coupled to score trajectories. Practically, early stopping at 50% completion reduces beam-search computation by 33.6% while retaining 98.9% of solutions, and degenerate-trajectory detection reduces SDFS computation by 65.3% with no solution loss.
What's missing
The study identifies a DSL (domain-specific language) coverage limitation where 229 of 400 evaluation tasks (57.25%) produce no valid transition from the input grid, universally failing beam search regardless of search budget. However, the paper does not discuss potential solutions to this DSL coverage gap or its implications for the broader feasibility of symbolic approaches to ARC-AGI.
What different sources said
- arXiv cs.LGCenter
Structural Grid Descriptors Predict Within-Task Solver Success on ARC-AGI
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