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Graph Representations for Higher-Order Logic and Theorem Proving

AAAI 2020 · Graph learning › GNN architectures · approach: Weisfeiler-Leman expressivity hierarchies · 69 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use a 12-hop GNN with subexpression sharing instead of the WaveNet baselineHOList proof search · HOList validationproofs closed: 32.65% -> 49.95%Helped
Use 12 message-passing hops rather than 0 hops (ablation)Subexpression-sharing GNN · HOList validationproofs closed: 40.86% -> 49.95%Helped
Add subexpression sharing rather than use a plain AST (ablation)12-hop GNN · HOList validationproofs closed: 45.67% -> 49.95%Helped
Blind variable names (ablation)Subexpression-sharing GNN · HOList validationproofs closed: 49.95% -> 37.36%Hurt
Add random edges (ablation)Subexpression-sharing GNN · HOList validationproofs closed: 49.95% -> 42.94%Hurt
Restrict message passing to top-down edges instead of both directions (ablation)Subexpression-sharing GNN · HOList validationproofs closed: 49.95% -> 48.40%Hurt
Restrict message passing to bottom-up edges instead of both directions (ablation)Subexpression-sharing GNN · HOList validationproofs closed: 49.95% -> 40.99%Hurt
Share only identical leaves rather than full subexpressions (ablation)GNN · HOList validationproofs closed: 41.76% -> 29.24% (0 Hops to 4 Hops)Hurt
Add variable blinding to leaf sharing (ablation)GNN · HOList validationproofs closed: 41.76% -> 31.78% (0 Hops); 29.24% -> 32.80% (4 Hops)Mixed

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