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  3. Unifying approach to uniform expressivity of graph neural ne
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Unifying approach to uniform expressivity of graph neural networks

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Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 0

Proof: unverified

Freshness: fresh

Source paper: Unifying approach to uniform expressivity of graph neural networks

PDF: https://arxiv.org/pdf/2602.18409v1

Source count: 0

Coverage: 17%

Last proof check: 2026-04-02T02:30:40.136Z

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Unifying approach to uniform expressivity of graph neural networks

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Last verification: 2026-04-02T02:30:40.136Z

Freshness: fresh

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References: 0

Sources: 0

Coverage: 17%

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Keep exploring

Prior Work
Recurrent Graph Neural Networks and Arithmetic Circuits
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Prior Work
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Score 2.0stable
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On the Expressive Power of GNNs for Boolean Satisfiability
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Beyond Message Passing: A Symbolic Alternative for Expressive and Interpretable Graph Learning
Score 7.0up
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Are Expressive Encoders Necessary for Discrete Graph Generation?
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Revealing Combinatorial Reasoning of GNNs via Graph Concept Bottleneck Layer
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SCL-GNN: Towards Generalizable Graph Neural Networks via Spurious Correlation Learning
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Competing Approach
Lost in Aggregation: On a Fundamental Expressivity Limit of Message-Passing Graph Neural Networks
Score 2.0stable

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