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Paper Citation Record · LEDGER

OpenGT: A Comprehensive Benchmark For Graph Transformers

As of 23 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2506.04765.

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

pith.paper-citation-record.v1
2506.04765 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:37:17.918143Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T08:53:49.813049Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:19:48.042489Z

Reference resolution

31 of 31 outbound references displayed

  • verified exact2
  • verified fuzzy6
  • unresolved23
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 898077ce-6a64-438b-aaa4-edcf33646288 · outbound

This paper cites Specformer: Spectral Graph Neural Networks Meet Transformers.

OpenGT: A Comprehensive Benchmark For Graph Transformers Specformer: Spectral Graph Neural Networks Meet Transformers

Reference 1

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source=pdf_text observed=2026-08-07T10:37:17.015113Z digest=sha256:94315460cacc4fe80a9c8eae82472360a9ec6220b16da516674807789df55ef2

Observation aac2664c-d79b-4dda-87c8-d95f7187fda1 · outbound

This paper cites A Generalization of Transformer Networks to Graphs.

OpenGT: A Comprehensive Benchmark For Graph Transformers A Generalization of Transformer Networks to Graphs

Reference 2

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source=pdf_text observed=2026-08-07T10:37:17.125036Z digest=sha256:acbfe40e2e69d25fd63fd63ab614e171c38f29e40b835381ba264bcda5eb9167

Observation 28a21685-3f56-4d00-8526-fee579dd094f · outbound

This paper cites Long range graph benchmark.Advances in Neural Information Processing Systems, 35:22326–22340, 2022.

OpenGT: A Comprehensive Benchmark For Graph Transformers Long range graph benchmark.Advances in Neural Information Processing Systems, 35:22326–22340, 2022

Reference 3

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source=pdf_text observed=2026-08-07T10:37:17.303548Z digest=sha256:b7ae7c795657ca4b31b752bcf5af05556d8d0a840f8dc643ec32f4828d3aeebd

Observation 0f6bbdbe-1f00-4782-94a8-86fb168560d8 · outbound

This paper cites Predict then Propagate: Graph Neural Networks meet Personalized PageRank.

OpenGT: A Comprehensive Benchmark For Graph Transformers Predict then Propagate: Graph Neural Networks meet Personalized PageRank

Reference 4

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source=pdf_text observed=2026-08-07T10:37:17.393239Z digest=sha256:cd473de46777516486b8069b65f8ce76fe83d161430bd440da70da699e4e64fb

Observation b126786a-6b14-4bf2-9af9-667af9dbcb72 · outbound

This paper cites Benchmarking positional encodings for gnns and graph transformers.arXiv preprint arXiv:2411.12732, 2024.

OpenGT: A Comprehensive Benchmark For Graph Transformers Benchmarking positional encodings for gnns and graph transformers.arXiv preprint arXiv:2411.12732, 2024

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T10:37:17.547970Z digest=sha256:65fc04656175594006096f4bc778f7a28e362fcffcbc1afe3e562e9ae1be805d

Observation 0917e71c-9c16-4b80-b240-776f57216b79 · outbound

This paper cites A generaliza- tion of vit/mlp-mixer to graphs.

OpenGT: A Comprehensive Benchmark For Graph Transformers A generaliza- tion of vit/mlp-mixer to graphs

Reference 6

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T10:37:17.703887Z digest=sha256:ef152686af9c2bc5ff621ad910bd72ab51c9e999598c50503c1f7fbc34b86126

Observation 9f167dbb-08a3-4251-a7e5-d8852dd02342 · outbound

This paper cites Open graph benchmark: Datasets for machine learning on graphs.Advances in neural information processing systems, 33:22118–22133, 2020.

OpenGT: A Comprehensive Benchmark For Graph Transformers Open graph benchmark: Datasets for machine learning on graphs.Advances in neural information processing systems, 33:22118–22133, 2020

Reference 7

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source=pdf_text observed=2026-08-07T10:37:17.815409Z digest=sha256:e70438110fb64c5423dbaf3655afd7a50140f524cfeeee340d8a0dbd1c04abc2

Observation 6601500a-5414-44bd-93e9-e223c0a75925 · outbound

This paper cites Zinc: a free tool to discover chemistry for biology.Journal of chemical information and modeling, 52(7):1757–1768, 2012.

OpenGT: A Comprehensive Benchmark For Graph Transformers Zinc: a free tool to discover chemistry for biology.Journal of chemical information and modeling, 52(7):1757–1768, 2012

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 56bf5f4b-05e7-4778-bba3-143072230824 · outbound

This paper cites The impact of positional encoding on length generalization in transformers.

OpenGT: A Comprehensive Benchmark For Graph Transformers The impact of positional encoding on length generalization in transformers

Reference 9

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source=pdf_text observed=2026-08-07T10:37:17.824241Z digest=sha256:a7e025d13f739defabf9e5e19c5604bdc5b240ae4e0d4000fdb13a7e87316bc8

Observation cfe3b133-d714-4811-963c-501e70fb749a · outbound

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

OpenGT: A Comprehensive Benchmark For Graph Transformers Semi-Supervised Classification with Graph Convolutional Networks

Reference 10

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Observation f8f820a4-4c21-44c5-a002-c3ed39b192df · outbound

This paper cites Rethinking graph transformers with spectral attention.Advances in Neural Information Processing Systems, 34:21618– 21629, 2021.

OpenGT: A Comprehensive Benchmark For Graph Transformers Rethinking graph transformers with spectral attention.Advances in Neural Information Processing Systems, 34:21618– 21629, 2021

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 89e765c8-2181-4430-aa4b-a8f835257a82 · outbound

This paper cites Graph Foundation Models: Concepts, Opportunities and Challenges.

OpenGT: A Comprehensive Benchmark For Graph Transformers Graph Foundation Models: Concepts, Opportunities and Challenges

Reference 12

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source=pdf_text observed=2026-08-07T10:37:17.837276Z digest=sha256:2120226e3713ecb9c6e8f802568fdb5844a0bc4d0e6ea6ce99c410046cb36319

Observation 2b12cc0f-037d-48f9-b87d-0ad3ce57eabd · outbound

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

OpenGT: A Comprehensive Benchmark For Graph Transformers Graph inductive biases in transformers without message passing

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a11b5338-59db-4175-8f88-2020bbbabb38 · outbound

This paper cites Geom-GCN: Geometric Graph Convolutional Networks.

OpenGT: A Comprehensive Benchmark For Graph Transformers Geom-GCN: Geometric Graph Convolutional Networks

Reference 14

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source=pdf_text observed=2026-08-07T10:37:17.846436Z digest=sha256:2cb9f59a1429edf4bd21c79243f9b9d8de4a8336744cb48b18592f1d9d70abe2

Observation 6827674b-9595-4102-b2fc-55fdebbb26fd · outbound

This paper cites Recipe for a general, powerful, scalable graph transformer.Advances in Neural Information Processing Systems, 35:14501–14515, 2022.

OpenGT: A Comprehensive Benchmark For Graph Transformers Recipe for a general, powerful, scalable graph transformer.Advances in Neural Information Processing Systems, 35:14501–14515, 2022

Reference 15

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Observation 79ac701f-6937-4d3d-9fef-eb53f36ac124 · outbound

This paper cites Gemsec: Graph embedding with self clustering.

OpenGT: A Comprehensive Benchmark For Graph Transformers Gemsec: Graph embedding with self clustering

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 5242cb86-dc58-413f-b86b-630c94a75144 · outbound

This paper cites Collective classification in network data.AI magazine, 29(3):93–93, 2008.

OpenGT: A Comprehensive Benchmark For Graph Transformers Collective classification in network data.AI magazine, 29(3):93–93, 2008

Reference 17

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source=pdf_text observed=2026-08-07T10:37:17.858690Z digest=sha256:3a07ff810fa2a4166155056a7bd7b9c0b624ab57c58ab8ccdd0c606b4cb97d07

Observation 3ab4701d-c977-4f54-ba5a-490407212429 · outbound

This paper cites Pitfalls of Graph Neural Network Evaluation.

OpenGT: A Comprehensive Benchmark For Graph Transformers Pitfalls of Graph Neural Network Evaluation

Reference 18

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Observation 28b4c126-bf7d-4db0-b167-b1b8071db7dd · outbound

This paper cites Graph transformers: A survey.arXiv preprint arXiv:2407.09777, 2024.

OpenGT: A Comprehensive Benchmark For Graph Transformers Graph transformers: A survey.arXiv preprint arXiv:2407.09777, 2024

Reference 19

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source=pdf_text observed=2026-08-07T10:37:17.866884Z digest=sha256:58c3b358c8a4454f96784f8e8bb0ac0eac66e8fdfc313e93a296b4cfd8dbac28

Observation 0790897c-a54a-41b3-9abe-e095fac40a99 · outbound

This paper cites Exphormer: Sparse transformers for graphs.

OpenGT: A Comprehensive Benchmark For Graph Transformers Exphormer: Sparse transformers for graphs

Reference 20

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Observation 47150826-e0d6-487f-91a7-efcd986cc07a · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

OpenGT: A Comprehensive Benchmark For Graph Transformers Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 21

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Observation ce09a41a-a2a2-415e-a72e-5ce28281ee79 · outbound

This paper cites Graph Attention Networks.

OpenGT: A Comprehensive Benchmark For Graph Transformers Graph Attention Networks

Reference 22

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Observation 9e47c625-158f-4dcf-971c-4b0e1c936124 · outbound

This paper cites Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks.

OpenGT: A Comprehensive Benchmark For Graph Transformers Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks

Reference 23

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source=pdf_text observed=2026-08-07T10:37:17.884128Z digest=sha256:87ccc54ac5560d9d2ae43c5f6614a2251c37581d309be468986d7c6d36aa0e42

Observation 7c4c368f-bcbe-44cb-8da9-4511ab62d529 · outbound

This paper cites Graph Triple Attention Network: A Decoupled Perspective.

OpenGT: A Comprehensive Benchmark For Graph Transformers Graph Triple Attention Network: A Decoupled Perspective

Reference 24

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local_arxiv, observed 2026-08-07T10:37:18.011379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T10:37:17.888465Z digest=sha256:9f85bea84b8b6630b67e404eccbc0ac1ef8c3d22b6c0403f45eda146f94e2ca0

Observation dcda4c92-df46-4fc8-ac4b-407036e8defc · outbound

This paper cites DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion.

OpenGT: A Comprehensive Benchmark For Graph Transformers DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion

Reference 25

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source=pdf_text observed=2026-08-07T10:37:17.892737Z digest=sha256:e74c67480795b303ea7329c0d11ea62372dbbb1ef9b2c178f50a1e303e6aa876

Observation 2de62c59-d81f-4613-9ba3-d64bf2c18bea · outbound

This paper cites Nodeformer: A scalable graph structure learning transformer for node classification.Advances in Neural Information Processing Systems, 35:27387–27401, 2022.

OpenGT: A Comprehensive Benchmark For Graph Transformers Nodeformer: A scalable graph structure learning transformer for node classification.Advances in Neural Information Processing Systems, 35:27387–27401, 2022

Reference 26

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source=pdf_text observed=2026-08-07T10:37:17.896955Z digest=sha256:bed5c547afb9b224e441063ee794fe60355b7bc54d26bf05118519767e4cc80e

Observation 5402d68a-398e-46f9-942d-80f4ae38197e · outbound

This paper cites Sgformer: Simplifying and empowering transformers for large-graph representations.Advances in Neural Information Processing Systems, 36:64753–64773, 2023.

OpenGT: A Comprehensive Benchmark For Graph Transformers Sgformer: Simplifying and empowering transformers for large-graph representations.Advances in Neural Information Processing Systems, 36:64753–64773, 2023

Reference 27

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source=pdf_text observed=2026-08-07T10:37:17.901191Z digest=sha256:41c313609107dd7c6ff875d8a30fb606857733b4314b905ba9576fbfd333c621

Observation 944e071d-271b-42fa-879e-670c3c0ca819 · outbound

This paper cites Less is More: on the Over-Globalizing Problem in Graph Transformers.

OpenGT: A Comprehensive Benchmark For Graph Transformers Less is More: on the Over-Globalizing Problem in Graph Transformers

Reference 28

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source=pdf_text observed=2026-08-07T10:37:17.905384Z digest=sha256:79602e9aefe3215a1b3e08c860130c9f3659761cd6b71c56532b7d2d11f61b3c

Observation e1db3f1c-ae10-4dec-a78b-289aa4cd0f8d · outbound

This paper cites Do transformers really perform badly for graph representation?Advances in neural information processing systems, 34:28877–28888, 2021.

OpenGT: A Comprehensive Benchmark For Graph Transformers Do transformers really perform badly for graph representation?Advances in neural information processing systems, 34:28877–28888, 2021

Reference 29

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source=pdf_text observed=2026-08-07T10:37:17.909828Z digest=sha256:d42ccb7cc9ff7b6931d3aa7b5e81a6a7e5ed5dec968a4e5e678928cecf298c74

Observation 59b32ae0-e629-43ce-b9dd-c22669ac0b0f · outbound

This paper cites Design space for graph neural networks.Advances in Neural Information Processing Systems, 33:17009–17021, 2020.

OpenGT: A Comprehensive Benchmark For Graph Transformers Design space for graph neural networks.Advances in Neural Information Processing Systems, 33:17009–17021, 2020

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T10:37:17.913747Z digest=sha256:f5f849bf07e006de556a4635f9ccfe6b56177741f37a25927e82a7c63ed44fe2

Observation 1277702b-ae65-41e4-bdb1-653f9fc908f5 · outbound

This paper cites Rethinking Positional Encoding.

OpenGT: A Comprehensive Benchmark For Graph Transformers Rethinking Positional Encoding

Reference 31

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source=pdf_text observed=2026-08-07T10:37:17.918143Z digest=sha256:863c2cb43760bdf73e16315f30e0136425bf62588b1582a7a11a8a1fea8cd898

Pith citing papers

Observation 6f425177-0193-4497-bc56-cb6d7ce0f753 · inbound

A Spectral Theory of Normalized Corrected GNN Propagation cites this paper.

A Spectral Theory of Normalized Corrected GNN Propagation OpenGT: A Comprehensive Benchmark For Graph Transformers

Reference 62

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arxiv_id, observed 2026-07-04T10:19:48.043779Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-26T08:53:49.813049Z digest=sha256:b65f3b144292f43f9bf74b1fa823d9853fb68fece5e9558edfc37c02015fde71