Paper Citation Record · LEDGER

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning

As of 14 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2507.07335.

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

pith.paper-citation-record.v1
2507.07335 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:48:01.291313Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

33 of 33 outbound references displayed

verified exact0
verified fuzzy26
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5d4e712a-189b-421b-83b4-8070c3745884 · outbound

This paper cites write newline.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning write newline

Reference 1

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Source-reported events for the cited work

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Observation 781cc67e-4c88-4914-a6bb-46d8f2dffd8b · outbound

This paper cites Constant curvature graph convolutional networks.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Constant curvature graph convolutional networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:06.667745Z

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Observation b5104c42-d424-4cf4-8d41-cec66d395606 · outbound

This paper cites Analyzing the expressive power of graph neural networks in a spectral perspective.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Analyzing the expressive power of graph neural networks in a spectral perspective

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:06.465071Z

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Observation 8bacda96-8f50-4e71-9899-cf2fd084b04e · outbound

This paper cites and Ganea, O.-E.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning and Ganea, O.-E

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:06.202783Z

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Observation 4532f48d-3094-4c31-ad24-b044cab50fbe · outbound

This paper cites Hyperbolic graph convolutional neural networks.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Hyperbolic graph convolutional neural networks

Reference 5

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Observation 9329015f-87f0-4e18-98b9-8562aa2589e4 · outbound

This paper cites Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:05.885599Z

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Observation a0ad0d4e-e6b8-46db-a87a-77bd276c3246 · outbound

This paper cites Joint adaptive feature smoothing and topology extraction via generalized pagerank gnns.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Joint adaptive feature smoothing and topology extraction via generalized pagerank gnns

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:05.647696Z

Source-reported events for the cited work

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Observation d879878e-e8e5-44c0-a05a-e50432fea858 · outbound

This paper cites Gbk-gnn: Gated bi-kernel graph neural networks for modeling both homophily and heterophily, 2022.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Gbk-gnn: Gated bi-kernel graph neural networks for modeling both homophily and heterophily, 2022

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:05.475525Z

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Observation 20b3cfbd-2efe-4212-aca1-eb5569eabc19 · outbound

This paper cites A Generalization of Transformer Networks to Graphs.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning A Generalization of Transformer Networks to Graphs

Reference 9

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Source-reported events for the cited work

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Observation 042473e5-0f14-40e2-8b49-58d964c665df · outbound

This paper cites E., Weichert, F., and Leskovec, J.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning E., Weichert, F., and Leskovec, J

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:05.327224Z

Source-reported events for the cited work

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Observation 09796dc9-41a5-4317-be90-f4d37388d3a1 · outbound

This paper cites Graphmore: Mitigating topological heterogeneity via mixture of riemannian experts.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Graphmore: Mitigating topological heterogeneity via mixture of riemannian experts

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:05.202487Z

Source-reported events for the cited work

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Observation a9d0ad1c-c09d-4f8f-aa10-bc53fd3d3c39 · outbound

This paper cites Inductive representation learning on large graphs.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Inductive representation learning on large graphs

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:04.991422Z

Source-reported events for the cited work

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Observation f25bcbb1-45bf-4e7c-a3c9-1eb51175bdb8 · outbound

This paper cites and Khasahmadi, A.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning and Khasahmadi, A

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:04.815304Z

Source-reported events for the cited work

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Observation f83ddea4-5666-40f3-af21-2c5e8b50ea16 · outbound

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Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-06T18:48:04.621508Z

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Observation 23763494-dcfc-42d1-84c6-70daf9c4d5e9 · outbound

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Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Unresolved cited work

Reference 15

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Source-reported events for the cited work

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Observation 31496d44-f4af-491c-a6f2-5f68c0577d31 · outbound

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Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Unresolved cited work

Reference 16

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Source-reported events for the cited work

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Observation 97bdc387-95a0-4612-b457-379019925ac1 · outbound

This paper cites Rethinking graph transformers with spectral attention.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Rethinking graph transformers with spectral attention

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:04.410577Z

Source-reported events for the cited work

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Observation 6dcfb563-9a3b-425d-8758-26e3363b5b04 · outbound

This paper cites Position: Graph foundation models are already here.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Position: Graph foundation models are already here

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:04.201347Z

Source-reported events for the cited work

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Observation c511b221-5817-4977-a0f2-c5a3f133d531 · outbound

This paper cites Motif-aware riemannian graph neural network with generative-contrastive learning.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Motif-aware riemannian graph neural network with generative-contrastive learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:03.992242Z

Source-reported events for the cited work

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Observation 16913230-e25a-431a-b604-bdb2a92671f4 · outbound

This paper cites Learning MLP s on graphs: A unified view of effectiveness and robustness and and efficiency.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Learning MLP s on graphs: A unified view of effectiveness and robustness and and efficiency

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:03.785700Z

Source-reported events for the cited work

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Observation 2eab9973-f79a-449e-9454-8500f491e825 · outbound

This paper cites Graph attention networks.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Graph attention networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:03.635626Z

Source-reported events for the cited work

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Observation 10534045-b81f-4ca3-ba76-eed48b241a6c · outbound

This paper cites R., and Wang, Z.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning R., and Wang, Z

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:03.426615Z

Source-reported events for the cited work

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Observation 4f1b0872-f49b-420e-88de-651939b03624 · outbound

This paper cites N., Wang, Z., Nallapati, R., Arnold, A., Xiang, B., Yu, P.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning N., Wang, Z., Nallapati, R., Arnold, A., Xiang, B., Yu, P

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:03.196365Z

Source-reported events for the cited work

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Observation ec0ed2ed-ed01-4d37-a372-8f6de856f4df · outbound

This paper cites Nodeformer: A scalable graph structure learning transformer for node classification.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Nodeformer: A scalable graph structure learning transformer for node classification

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:02.994439Z

Source-reported events for the cited work

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Observation 579cfe21-f1dd-44c8-9cae-4c8714a013e6 · outbound

This paper cites Difformer: Scalable (graph) transformers induced by energy constrained diffusion.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Difformer: Scalable (graph) transformers induced by energy constrained diffusion

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:02.805058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6059aa65-dd57-4832-b9a8-c28ec7366a10 · outbound

This paper cites Sgformer: Simplifying and empowering transformers for large-graph representations.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Sgformer: Simplifying and empowering transformers for large-graph representations

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:02.584623Z

Source-reported events for the cited work

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Observation 4da31432-dc86-4565-ae39-13aa0368157c · outbound

This paper cites Graphmetro: Mitigating complex graph distribution shifts via mixture of aligned experts.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Graphmetro: Mitigating complex graph distribution shifts via mixture of aligned experts

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:02.307802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 67700f8c-ae21-40e7-b83b-bf4b55b7b098 · outbound

This paper cites Pseudo-riemannian graph convolutional networks.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Pseudo-riemannian graph convolutional networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:02.099669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d195aa5c-6ba5-4063-b4e2-49db94771130 · outbound

This paper cites Graphsaint: Graph sampling based inductive learning method.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Graphsaint: Graph sampling based inductive learning method

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:01.980087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 15dd4ea4-0cff-4957-822f-d0fd940c25e9 · outbound

This paper cites Lorentzian graph convolutional networks.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Lorentzian graph convolutional networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:01.862737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 70035f81-0b75-4d9d-8cc1-7d278de2583a · outbound

This paper cites Graph-Bert: Only Attention is Needed for Learning Graph Representations.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Graph-Bert: Only Attention is Needed for Learning Graph Representations

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T18:48:01.074300Z

Source-reported events for the cited work

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Observation 943a5f65-d939-4ce4-99e0-b5acb9c30cbc · outbound

This paper cites Linear attention via orthogonal memory, 2023.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Linear attention via orthogonal memory, 2023

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T18:48:01.168647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79cae2da-5b9f-40f2-a053-3c2b98d2967d · outbound

This paper cites Graph-less neural networks: Teaching old mlps new tricks via distillation.

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning Graph-less neural networks: Teaching old mlps new tricks via distillation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:48:01.592236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.