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Reasoning traces with identical final answers and identical entropy curves can conceal radically different internal dynamics, from protracted multi-hypothesis competition to sudden late-stage revision.
Turns out, the fancy learnable restriction maps in Sheaf Neural Networks might not be worth the complexity – a simple identity mapping works just as well for mitigating oversmoothing on heterophilic graphs.
