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This ICML paper introduces recursive models that recursively invoke themselves to solve subtasks in isolated contexts, proving they can surpass context-bounded autoregressive models for long-horizon reasoning. Experiments on SAT solving and Go game-tree search show improved accuracy with small active contexts.
Proposes interaction locality, a task-geometry-aware framework for measuring whether information flow in spatial reasoning models stays within local cells or crosses into global structure, and applies it to HRM, TRM, and MTU3D models on grid benchmarks and embodied 3D grounding.