Bilevel graph structure learning gains largely originate from inner-loop training dynamics with implicit regularization, not graph rewiring, as isolated by a frozen-graph control that accounts for 37-101% of reported improvements.
Learning latent graph structures and their uncertainty
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Bilevel Graph Structure Learning, Revisited: Inner-Channel Origins of the Reported Gain
Bilevel graph structure learning gains largely originate from inner-loop training dynamics with implicit regularization, not graph rewiring, as isolated by a frozen-graph control that accounts for 37-101% of reported improvements.