Paper Citation Record · LEDGER

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks

As of 17 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2509.06777.

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

pith.paper-citation-record.v1
2509.06777 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:12:25.085956Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

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verified fuzzy25
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External citation measurements

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Outbound references

Observation 1df276cb-cecc-401f-8e48-4f33b120d2d1 · outbound

This paper cites The graph neural network model,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks The graph neural network model,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T23:12:21.840457Z

Source-reported events for the cited work

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Observation 02457db2-a07b-42f2-a39b-fe8689f60817 · outbound

This paper cites Simplifying graph convolutional networks,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Simplifying graph convolutional networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:30.137852Z

Source-reported events for the cited work

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Observation ee1cf0f8-0a36-4b72-a68a-5da500a58644 · outbound

This paper cites Principal neighbourhood aggregation for graph nets,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Principal neighbourhood aggregation for graph nets,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:29.854802Z

Source-reported events for the cited work

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Observation 55cf8484-e154-41bd-95d4-24695f718e2f · outbound

This paper cites Benchmarking graph neural networks,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Benchmarking graph neural networks,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:29.551871Z

Source-reported events for the cited work

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Observation 96857336-75a6-4306-8a6d-99925d2f915f · outbound

This paper cites Long range graph benchmark,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Long range graph benchmark,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:29.417507Z

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Observation 4dfb6755-0948-4523-b9f4-4fd4814bb174 · outbound

This paper cites Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:29.268189Z

Source-reported events for the cited work

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Observation 7ce02652-ffc2-45ff-bf51-f2e3d1801396 · outbound

This paper cites On the Bottleneck of Graph Neural Networks and its Practical Implications.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks On the Bottleneck of Graph Neural Networks and its Practical Implications

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T23:12:22.270982Z

Source-reported events for the cited work

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Observation 91e14ec1-b4ce-412e-8afd-ea739c585dd4 · outbound

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

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks On over-squashing in message passing neural networks: The impact of width, depth, and topology,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:29.123380Z

Source-reported events for the cited work

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Observation 03e8f1f0-d600-4858-9417-cce212c740fd · outbound

This paper cites Drew: Dynamically rewired message passing with delay,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Drew: Dynamically rewired message passing with delay,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:29.014336Z

Source-reported events for the cited work

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Observation f644d9d2-3ff2-4caf-947f-f5c7d662a1ba · outbound

This paper cites FoSR: First-order spectral rewiring for addressing oversquashing in GNNs.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks FoSR: First-order spectral rewiring for addressing oversquashing in GNNs

Reference 11

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Observation 02147726-ca9f-4eea-bdbc-7e1234635436 · outbound

This paper cites DiffWire: Inductive Graph Rewiring via the Lov\'asz Bound.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks DiffWire: Inductive Graph Rewiring via the Lov\'asz Bound

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T23:12:22.650980Z

Source-reported events for the cited work

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Observation 99ff6e6f-1e47-4235-a0a6-abcd991f4a9d · outbound

This paper cites Locality-Aware Graph-Rewiring in GNNs.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Locality-Aware Graph-Rewiring in GNNs

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-04T23:12:25.462410Z

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Observation 74938f18-892d-416e-82e0-33301f96f266 · outbound

This paper cites Understanding oversquashing in gnns through the lens of effective resistance,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Understanding oversquashing in gnns through the lens of effective resistance,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:28.875146Z

Source-reported events for the cited work

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Observation 427649f7-3708-45e3-b5b8-86ab3d8690da · outbound

This paper cites Probabilistically Rewired Message-Passing Neural Networks.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Probabilistically Rewired Message-Passing Neural Networks

Reference 15

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Source-reported events for the cited work

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Observation bd223bfd-a3e6-495c-8691-be768362f0fd · outbound

This paper cites A Generalization of Transformer Networks to Graphs.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks A Generalization of Transformer Networks to Graphs

Reference 16

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Source-reported events for the cited work

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Observation 329df158-a4cf-4e29-bc8d-141a9bb2e091 · outbound

This paper cites PANDA: Expanded width-aware message passing beyond rewiring,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks PANDA: Expanded width-aware message passing beyond rewiring,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:28.754137Z

Source-reported events for the cited work

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Observation 4222b788-319e-4760-8ea1-f93191e11f0c · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Semi-Supervised Classification with Graph Convolutional Networks

Reference 18

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Source-reported events for the cited work

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Observation e850f0f1-becd-42a4-8f24-b9c4c0e07c0e · outbound

This paper cites Graph Attention Networks.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Graph Attention Networks

Reference 19

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Source-reported events for the cited work

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Observation dc7180f3-c1fe-4ffc-829f-365d9c1f9e62 · outbound

This paper cites Simple and deep graph convolutional networks,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Simple and deep graph convolutional networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:28.608138Z

Source-reported events for the cited work

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Observation b21b00aa-7510-4652-9ae1-b3643062a69b · outbound

This paper cites GwAC: GNNs with asynchronous communication,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks GwAC: GNNs with asynchronous communication,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:28.464177Z

Source-reported events for the cited work

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Observation 5a7cf92f-beb9-43ae-853f-be84d49135a0 · outbound

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

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks How does over-squashing affect the power of GNNs?

Reference 22

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Observation 9b5c6070-61d9-4bd3-a702-22c4a26c07e4 · outbound

This paper cites DropEdge: Towards Deep Graph Convolutional Networks on Node Classification.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 23

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Source-reported events for the cited work

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Observation 0cb148af-ff2c-4aa5-a58a-b550a0efb230 · outbound

This paper cites Diffusion improves graph learning,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Diffusion improves graph learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:28.272189Z

Source-reported events for the cited work

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Observation 743ac231-184e-40eb-a30e-01825c19c2ab · outbound

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

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Revisiting over-smoothing and over-squashing using ollivier-ricci curvature,

Reference 25

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Observation 03451722-8c66-4cf7-879f-e7d42ceb4a94 · outbound

This paper cites On the trade-off between over-smoothing and over-squashing in deep graph neural networks,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks On the trade-off between over-smoothing and over-squashing in deep graph neural networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:27.944369Z

Source-reported events for the cited work

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Observation 5c16d955-ac48-4e49-ac4d-98dadc7726b8 · outbound

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

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Oversquashing in gnns through the lens of information contraction and graph expansion,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:27.738505Z

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.

Observation 0c0047e8-b49d-4339-8fe4-657a5011b937 · outbound

This paper cites Cooperative graph neural networks,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Cooperative graph neural networks,

Reference 28

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Source-reported events for the cited work

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Observation 44f1281a-6ca0-4440-9edc-5568a1690fd9 · outbound

This paper cites Improving message-passing gnns by asynchronous aggregation,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Improving message-passing gnns by asynchronous aggregation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:27.324506Z

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Observation c58d916b-fe42-4c56-bbf4-3bb6e2080c00 · outbound

This paper cites Expander graph propagation,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Expander graph propagation,

Reference 30

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Source-reported events for the cited work

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Observation fa8ba451-dabc-4bb7-a5fc-bff7b5412ee8 · outbound

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

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Understanding over-squashing and bottlenecks on graphs via curvature

Reference 31

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Observation 5f82056e-04b0-4e03-a2b5-0e0a5b4db9cb · outbound

This paper cites Inductive representation learning on large graphs,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Inductive representation learning on large graphs,

Reference 32

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Source-reported events for the cited work

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Observation 46badaef-09db-4a61-94da-b106b506d120 · outbound

This paper cites GraphSAINT: Graph Sampling Based Inductive Learning Method.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 33

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Observation e2aadfbe-e9be-4eca-b076-36d9e9b9db65 · outbound

This paper cites Analyzing affiliation networks,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Analyzing affiliation networks,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:26.481136Z

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Observation 7d6623c3-155f-4256-92a7-f69b0a1e6bab · outbound

This paper cites A set of measures of centrality based on betweenness.(1977),.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks A set of measures of centrality based on betweenness.(1977),

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:26.332632Z

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Observation a6947725-0144-4005-8740-6aa0ac0b8dca · outbound

This paper cites Centrality in social networks: Conceptual clarification,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Centrality in social networks: Conceptual clarification,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:26.211304Z

Source-reported events for the cited work

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Observation 690fd603-bf32-49ef-9084-33e218fd8cbc · outbound

This paper cites Universal behavior of load distribution in scale-free networks,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Universal behavior of load distribution in scale-free networks,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:26.053276Z

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Observation 249fe148-e655-4e89-99d8-95ee0b59d117 · outbound

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

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks The pagerank citation ranking: Bringing order to the web

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:25.905837Z

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Observation e0cc3309-6dbd-45d7-abf9-9c995ed6666a · outbound

This paper cites How Powerful are Graph Neural Networks?.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks How Powerful are Graph Neural Networks?

Reference 39

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Source-reported events for the cited work

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Observation 9624e4d9-83fa-4334-856a-fcfaa1c2cd26 · outbound

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

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks TUDataset: A collection of benchmark datasets for learning with graphs

Reference 40

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This paper cites Minimizing effective resistance of a graph,.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Minimizing effective resistance of a graph,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:12:25.786933Z

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Observation be32f062-466c-429e-9ec8-f7335de5d687 · outbound

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Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-04T23:12:25.672641Z

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Pith citing papers

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