Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks | Paper Citation Record

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This paper cites Lignn: Graph neural networks at linkedin,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Lignn: Graph neural networks at linkedin,

Reference 1

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Observation 95166cee-a8ff-4625-ac8c-7f551a958531 · outbound

This paper cites A graph and attentive multi-path convolutional network for traffic prediction,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks A graph and attentive multi-path convolutional network for traffic prediction,

Reference 2

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Observation f7913b4f-b41d-4296-9d43-fbee910e9329 · outbound

This paper cites Gnngo3d: Protein function prediction based on 3d structure and functional hierarchy learning,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Gnngo3d: Protein function prediction based on 3d structure and functional hierarchy learning,

Reference 3

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Observation 99ea3395-8047-4f5d-aee7-dcc742c1ad90 · outbound

This paper cites Neural message passing for quantum chemistry,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Neural message passing for quantum chemistry,

Reference 4

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Observation 86852589-8f3e-4524-bbd9-a18147aba45d · outbound

This paper cites Inductive representation learning on large graphs,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Inductive representation learning on large graphs,

Reference 5

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Observation c0e41d01-f3a5-46f0-81d5-8237dd0fbb42 · outbound

This paper cites Deeper insights into graph convolu- tional networks for semi-supervised learning,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Deeper insights into graph convolu- tional networks for semi-supervised learning,

Reference 6

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Observation b27be4ef-15e6-4988-93e1-80584e5fa6e5 · outbound

This paper cites On the bottleneck of graph neural networks and its practical implications,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks On the bottleneck of graph neural networks and its practical implications,

Reference 7

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This paper cites Graph-coupled oscillator networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Graph-coupled oscillator networks,

Reference 8

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Observation 2ee94866-ce37-4412-8e43-6b691464e4cc · outbound

This paper cites Towards deep attention in graph neural networks: problems and remedies,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Towards deep attention in graph neural networks: problems and remedies,

Reference 9

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Observation 145c5140-7127-4cf9-b47d-8b508d5e23b4 · outbound

This paper cites Channel-attentive graph neural JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2021 12 networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Channel-attentive graph neural JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2021 12 networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:03:04.323469Z

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Observation d2990801-e3a2-4f40-a429-5841f1684370 · outbound

This paper cites Representation learning on graphs with jumping knowledge networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Representation learning on graphs with jumping knowledge networks,

Reference 11

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Observation 8b6ccd25-c6d9-4710-9453-342cba7b918a · outbound

This paper cites Simple and deep graph convolutional networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Simple and deep graph convolutional networks,

Reference 12

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Observation 94bb363e-1d78-45e1-950f-a77b094eb2b0 · outbound

This paper cites Do transformers really perform bad for graph representation?.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Do transformers really perform bad for graph representation?

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:03:03.344802Z

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Observation f28a3b27-98f0-4376-bf3c-8802ab31fe69 · outbound

This paper cites Graph inductive biases in transformers without message passing,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Graph inductive biases in transformers without message passing,

Reference 14

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Observation af75cf02-2354-4299-a9e2-8b9e8f241cbd · outbound

This paper cites Attending to graph transformers,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Attending to graph transformers,

Reference 15

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Observation eeb7755a-9d2a-4faa-b953-9caefc53f8aa · outbound

This paper cites Understanding over-squashing and bottlenecks on graphs via curvature,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Understanding over-squashing and bottlenecks on graphs via curvature,

Reference 16

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Observation 2feb82a7-ece8-4a4c-8296-31d97c565edf · outbound

This paper cites FoSR: First-order spec- tral rewiring for addressing oversquashing in GNNs,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks FoSR: First-order spec- tral rewiring for addressing oversquashing in GNNs,

Reference 17

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Observation ba2b3e59-49c8-4717-a51d-4611be2de801 · outbound

This paper cites Revisiting over-smoothing and over-squashing using ollivier- ricci curvature,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Revisiting over-smoothing and over-squashing using ollivier- ricci curvature,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:03:01.615992Z

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Observation be5677ac-0787-42ae-9ce7-eba4f7a62a3b · outbound

This paper cites Understanding over- squashing in gnns through the lens of effective resistance,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Understanding over- squashing in gnns through the lens of effective resistance,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:03:01.364642Z

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Observation b880ff2d-faf3-4bfb-ac3d-c1040911d743 · outbound

This paper cites Dif- fWire: Inductive Graph Rewiring via the Lovász Bound,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Dif- fWire: Inductive Graph Rewiring via the Lovász Bound,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:03:01.044979Z

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Observation c2ce5104-11b2-46c2-a133-9372ab12e6e6 · outbound

This paper cites Rewiring with po- sitional encodings for graph neural networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Rewiring with po- sitional encodings for graph neural networks,

Reference 21

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Observation 52cccd02-cf47-4d0c-bdd3-5f5677b68772 · outbound

This paper cites Locality-aware graph rewiring in GNNs,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Locality-aware graph rewiring in GNNs,

Reference 22

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Observation 63b450d4-a828-454f-9f69-0efa1d3ccf53 · outbound

This paper cites On over-squashing in message passing neural networks: the impact of width, depth, and topology,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks On over-squashing in message passing neural networks: the impact of width, depth, and topology,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:03:00.169118Z

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Observation 503044c2-b5bd-44a6-86e2-5643f9a0c27d · outbound

This paper cites Panda: expanded width-aware message passing beyond rewiring,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Panda: expanded width-aware message passing beyond rewiring,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:59.923179Z

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Observation 8c11495f-3233-4d65-9707-a3669ce1262d · outbound

This paper cites How does over-squashing affect the power of GNNs?.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks How does over-squashing affect the power of GNNs?

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:59.514910Z

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Observation 9991c168-b362-4dc2-a0cc-c4180bb59265 · outbound

This paper cites Oversquashing in gnns through the lens of information contraction and graph expansion,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Oversquashing in gnns through the lens of information contraction and graph expansion,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:59.283629Z

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Observation 9a48eafa-a6c5-45ca-a7b8-7ada873b91e4 · outbound

This paper cites Graph rewiring and preprocessing for graph neural networks based on effective resistance,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Graph rewiring and preprocessing for graph neural networks based on effective resistance,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:59.057682Z

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Observation 11ebf6e9-40e3-4ed7-aaed-c35b20769e94 · outbound

This paper cites Diffusion improves graph learning,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Diffusion improves graph learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:58.864856Z

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Observation 7498984c-3ed9-4f41-9913-1ad0859dd1c8 · outbound

This paper cites Probabilistically rewired message-passing neural networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Probabilistically rewired message-passing neural networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:58.581683Z

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Observation 9d425f2e-1ecb-4b68-80fe-a206591f9bf4 · outbound

This paper cites Expander graph propagation,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Expander graph propagation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:58.347444Z

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Observation b4cf81a2-f8e4-4a87-8884-e90576a2e757 · outbound

This paper cites Cayley graph propagation,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Cayley graph propagation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:58.192538Z

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Observation 518c10d5-cb3c-456a-afbb-cbea9e44b317 · outbound

This paper cites Delaunay graph: Addressing over-squashing and over-smoothing using delaunay triangulation,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Delaunay graph: Addressing over-squashing and over-smoothing using delaunay triangulation,

Reference 32

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Observation 683cf230-5627-497a-beaa-276def3258a9 · outbound

This paper cites On the connection between mpnn and graph transformer,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks On the connection between mpnn and graph transformer,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:57.734825Z

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Observation d264743a-11e9-4fe7-b3bf-a637b3b2372d · outbound

This paper cites Un- derstanding virtual nodes: Oversquashing and node heterogeneity,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Un- derstanding virtual nodes: Oversquashing and node heterogeneity,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:57.513395Z

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Observation abe6a80d-bb01-4ce9-ad9b-d996545a91a8 · outbound

This paper cites An analysis of virtual nodes in graph neural networks for link prediction,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks An analysis of virtual nodes in graph neural networks for link prediction,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:57.242534Z

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Observation 61556ef5-3180-450f-bf59-b87f29b350d1 · outbound

This paper cites VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification

Reference 36

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Observation 16a40f70-0282-44ef-aec5-8a77e385e28c · outbound

This paper cites Improving equivariant graph neural networks on large geometric graphs via virtual nodes learning,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Improving equivariant graph neural networks on large geometric graphs via virtual nodes learning,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:57.074822Z

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Observation 8695b6e8-e544-4953-829d-07d9c7e45268 · outbound

This paper cites E(n) equivariant graph neural networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks E(n) equivariant graph neural networks,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:56.818374Z

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Observation b84bf950-2cd2-4827-96de-e978ad41d0bb · outbound

This paper cites Probabilistic graph rewiring via virtual nodes,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Probabilistic graph rewiring via virtual nodes,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:56.618527Z

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Observation 2ce360ab-28b1-4a7e-a32c-dff637fc21a2 · outbound

This paper cites A faster algorithm for betweenness centrality*,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks A faster algorithm for betweenness centrality*,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:56.324752Z

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Observation ba5f7440-5e58-42bc-ab16-e5aa62cba7ff · outbound

This paper cites Scientific collaboration networks. ii. shortest paths, weighted networks, and centrality,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Scientific collaboration networks. ii. shortest paths, weighted networks, and centrality,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:55.974822Z

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Observation 8a751c50-52c8-4c2c-b6e0-e216c635c71f · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Semi-supervised classification with graph convolutional networks,

Reference 42

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Observation 4c96518a-98d1-4cb3-9962-0436b4f6c7ce · outbound

This paper cites How powerful are graph neural networks?.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks How powerful are graph neural networks?

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-05T15:02:50.487659Z

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Observation 04263f78-18a4-4791-ac29-8f5c4b80ad02 · outbound

This paper cites Graph attention networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Graph attention networks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:55.498558Z

Source-reported events for the cited work

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Observation 759fcd1a-9c0c-4f0d-9543-095d71e1d49f · outbound

This paper cites The pagerank citation ranking: Bringing order to the web.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks The pagerank citation ranking: Bringing order to the web

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:55.293960Z

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Observation 9748ab18-d8ba-4301-886b-7b1bf11b08ad · outbound

This paper cites Near linear time algorithm to detect community structures in large-scale networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Near linear time algorithm to detect community structures in large-scale networks,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:55.043165Z

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Observation 63bf7b19-e573-47eb-8a9a-b6bc0b1dfac5 · outbound

This paper cites Attention is all you need,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Attention is all you need,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:54.826239Z

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Observation cc495b78-da42-491a-9078-7d28d23d18cb · outbound

This paper cites Tudataset: A collection of benchmark datasets for learning with graphs,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Tudataset: A collection of benchmark datasets for learning with graphs,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:54.504961Z

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Observation 55e26a53-5b03-40e2-86f0-fb2d691ed2ba · outbound

This paper cites Geom-gcn: Geometric graph convolutional networks,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Geom-gcn: Geometric graph convolutional networks,

Reference 49

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This paper cites Collective classification in network data,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Collective classification in network data,

Reference 50

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Observation d0d0c860-a361-4d08-985e-6c21276c56b7 · outbound

This paper cites Adam: A method for stochastic optimization,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Adam: A method for stochastic optimization,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:53.679485Z

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Observation 848ceffe-3b9a-48d0-b97b-e7c2ecfc2128 · outbound

This paper cites Batch normalization: accelerating deep net- work training by reducing internal covariate shift,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Batch normalization: accelerating deep net- work training by reducing internal covariate shift,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:53.244382Z

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Observation 21c3ccfa-a961-4dcc-ae41-ece0853004f3 · outbound

This paper cites Minimizing effective resistance of a graph,.

Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks Minimizing effective resistance of a graph,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:02:52.894934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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