Paper Citation Record · LEDGER

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts

As of 15 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2412.11085.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.11085 v1

Coverage vector

measured 49 of 49 reference resolution

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

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External citation measurements

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Outbound references

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GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts Unresolved cited work

Reference 1

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This paper cites M.; Bruna, J.; LeCun, Y.; Szlam, A.; and Vandergheynst, P.

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts M.; Bruna, J.; LeCun, Y.; Szlam, A.; and Vandergheynst, P

Reference 3

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This paper cites Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning.

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning

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Reference 7

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Reference 10

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Reference 11

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Reference 12

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This paper cites Node-wise Filtering in Graph Neural Networks: A Mixture of Experts Approach.

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts Node-wise Filtering in Graph Neural Networks: A Mixture of Experts Approach

Reference 13

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GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts A.; Jordan, M

Reference 17

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GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts Adam: A Method for Stochastic Optimization

Reference 19

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GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts N.; and Welling, M

Reference 20

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GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts Graph Foundation Models: Concepts, Opportunities and Challenges

Reference 21

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GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts Pitfalls of Graph Neural Network Evaluation

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GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts N.; Wang, Z.; Nallapati, R.; Arnold, A.; Xiang, B.; Yu, P

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GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts C.; Liu, J.; King, I.; and Ying, R

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GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts Hyperbolic Graph Neural Networks: A Review of Methods and Applications

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Pith citing papers

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