One Model, Two Roles: Emergent Specialization in a Shared Recurrent Transformer

In three linesStudy of a shared-weight recurrent Transformer architecture (AIR) that develops two distinct roles without modular partitioning. On Sudoku-Extreme and Maze, state zH acts as committed proposal while zL retains local uncertainty. Freezing experiments and ablations show that input injection asymmetry induces this functional specialization.

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