Paper Citation Record · LEDGER

A Theory for Compressibility of Graph Transformers for Transductive Learning

As of 18 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 3 inbound Pith citation observations for arXiv:2411.13028.

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

pith.paper-citation-record.v1
2411.13028 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:05:46.879487Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:22:32.375169Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T04:55:23.296689Z

Reference resolution

45 of 45 outbound references displayed

verified exact0
verified fuzzy3
unresolved42
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 726295ea-2664-4513-9055-07a51639c0fe · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:05:47.442197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 52c1a057-2c06-4485-996d-b4f9998bb52f · outbound

This paper cites and Price, E.

A Theory for Compressibility of Graph Transformers for Transductive Learning and Price, E

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:05:47.432645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e91b557a-0937-405c-8d96-bb599f087c94 · outbound

This paper cites Polynormer: Polynomial-Expressive Graph Transformer in Linear Time.

A Theory for Compressibility of Graph Transformers for Transductive Learning Polynormer: Polynomial-Expressive Graph Transformer in Linear Time

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.730973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f73ad74d-0324-4d8c-9471-d8dc17ee1c93 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

A Theory for Compressibility of Graph Transformers for Transductive Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.735015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e51d70c-6d3e-4516-a0cd-074da7aa8a95 · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:05:47.423019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f6f43ea0-016f-48f1-b793-0a24bb15107c · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

A Theory for Compressibility of Graph Transformers for Transductive Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.742691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d00ffff-eebe-47d4-926a-69da9ad70a28 · outbound

This paper cites A Generalization of Transformer Networks to Graphs.

A Theory for Compressibility of Graph Transformers for Transductive Learning A Generalization of Transformer Networks to Graphs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.746635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e863078e-2048-4497-910b-04a1e2071fab · outbound

This paper cites and Lenssen, J.

A Theory for Compressibility of Graph Transformers for Transductive Learning and Lenssen, J

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.750020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa458707-0ece-49c8-b58e-650e2b6a952d · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.753611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb047a84-49c7-4002-a96e-bb93e93e5d87 · outbound

This paper cites OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs.

A Theory for Compressibility of Graph Transformers for Transductive Learning OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.756901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 413ba3b7-3668-46e7-aab6-1a8612d9e95f · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.760621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4686c4c3-9a4d-4883-808b-db285a305924 · outbound

This paper cites and Shakhnarovich, G.

A Theory for Compressibility of Graph Transformers for Transductive Learning and Shakhnarovich, G

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.764764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28ca2c38-86a2-4b8e-9b0c-7ff707cf9de1 · outbound

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

A Theory for Compressibility of Graph Transformers for Transductive Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.767940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4552ca4e-142a-4712-a62f-0045680b330d · outbound

This paper cites Rethinking Graph Transformers with Spectral Attention.

A Theory for Compressibility of Graph Transformers for Transductive Learning Rethinking Graph Transformers with Spectral Attention

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.771587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4192465-96b8-453f-b989-adbf9707cb5a · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:05:47.387362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e438c3b7-fe55-4df0-8a73-d28372071b9c · outbound

This paper cites On the Expressive Power of Self-Attention Matrices.

A Theory for Compressibility of Graph Transformers for Transductive Learning On the Expressive Power of Self-Attention Matrices

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.778144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87d6db91-d27a-4c05-bee3-26dfb9d01d8b · outbound

This paper cites Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities.

A Theory for Compressibility of Graph Transformers for Transductive Learning Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.782138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16781d6d-d5b5-42e8-b749-0c9c041c715e · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

A Theory for Compressibility of Graph Transformers for Transductive Learning SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.785980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2543d69a-b214-440a-9901-7572b5445306 · outbound

This paper cites Decoupled Weight Decay Regularization.

A Theory for Compressibility of Graph Transformers for Transductive Learning Decoupled Weight Decay Regularization

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.790234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4e2f6c4-5333-4641-9b95-9622595d5936 · outbound

This paper cites What graph neural networks cannot learn: depth vs width.

A Theory for Compressibility of Graph Transformers for Transductive Learning What graph neural networks cannot learn: depth vs width

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.794392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d60be399-b499-4561-9b87-50d7ac2cc23e · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:05:47.377017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7aaaadd8-bd1c-4dde-916c-1a306ae61845 · outbound

This paper cites Attending to Graph Transformers.

A Theory for Compressibility of Graph Transformers for Transductive Learning Attending to Graph Transformers

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.801789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44ab4783-73a8-4fd2-a5cf-bd6ce32b8bc4 · outbound

This paper cites P., and Yasuda, T.

A Theory for Compressibility of Graph Transformers for Transductive Learning P., and Yasuda, T

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:05:47.366207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 66f46084-30e1-48ae-afb0-311c4b39305a · outbound

This paper cites Revisiting Graph Neural Networks: All We Have is Low-Pass Filters.

A Theory for Compressibility of Graph Transformers for Transductive Learning Revisiting Graph Neural Networks: All We Have is Low-Pass Filters

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.808690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcc4bf8b-7030-482f-94f3-817a642cc571 · outbound

This paper cites Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.

A Theory for Compressibility of Graph Transformers for Transductive Learning Graph Neural Networks Exponentially Lose Expressive Power for Node Classification

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.812455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07605304-cfbb-4681-bcb1-6bbd7a12e925 · outbound

This paper cites A critical look at the evaluation of GNNs under heterophily: Are we really making progress?.

A Theory for Compressibility of Graph Transformers for Transductive Learning A critical look at the evaluation of GNNs under heterophily: Are we really making progress?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.816309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88b9c471-4d58-41e0-941e-5aad642bf858 · outbound

This paper cites P., Luu, A.

A Theory for Compressibility of Graph Transformers for Transductive Learning P., Luu, A

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.820314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27a6a294-9f3a-42b6-8f9c-34fb8129631a · outbound

This paper cites Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph.

A Theory for Compressibility of Graph Transformers for Transductive Learning Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.823721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91ddec12-cd19-477e-a5da-070f062534e9 · outbound

This paper cites Understanding Transformer Reasoning Capabilities via Graph Algorithms.

A Theory for Compressibility of Graph Transformers for Transductive Learning Understanding Transformer Reasoning Capabilities via Graph Algorithms

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.827097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab793125-4774-4c0d-be2a-16eed88b2c64 · outbound

This paper cites Transformers, parallel computation, and logarithmic depth.

A Theory for Compressibility of Graph Transformers for Transductive Learning Transformers, parallel computation, and logarithmic depth

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.830380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 392fca21-a569-45bb-a378-152e09183ea2 · outbound

This paper cites J., and Telgarsky, M.

A Theory for Compressibility of Graph Transformers for Transductive Learning J., and Telgarsky, M

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:05:47.348450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 99b30cdf-42a9-448a-800f-7a0bff882693 · outbound

This paper cites Pitfalls of Graph Neural Network Evaluation.

A Theory for Compressibility of Graph Transformers for Transductive Learning Pitfalls of Graph Neural Network Evaluation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.836867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec5c4046-b428-4cfa-aac7-fc78a86e5368 · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:05:47.337846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8629bff1-af7f-4c28-a773-2cd4d9611515 · outbound

This paper cites J., and Sinop, A.

A Theory for Compressibility of Graph Transformers for Transductive Learning J., and Sinop, A

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.843474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd8c1e6b-7912-440a-ac74-bde8af4158d6 · outbound

This paper cites N., Kaiser, L., and Polosukhin, I.

A Theory for Compressibility of Graph Transformers for Transductive Learning N., Kaiser, L., and Polosukhin, I

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.846880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78a4aa94-d3d7-476c-a0e3-96fa5f679c4e · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.849929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3126caa-14a9-4315-930f-84b33ebbbf4a · outbound

This paper cites Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks.

A Theory for Compressibility of Graph Transformers for Transductive Learning Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.852927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 952657f3-3394-4ea8-b6da-6626f01fb363 · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

A Theory for Compressibility of Graph Transformers for Transductive Learning Linformer: Self-Attention with Linear Complexity

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.856049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf6274b9-93cc-4cc7-a559-7ad564acd163 · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:05:47.307089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 35be007d-a992-4bb8-8cfa-2605db5f9718 · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.861996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98f95dc5-a8b8-42b8-8da6-f00a21135288 · outbound

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

A Theory for Compressibility of Graph Transformers for Transductive Learning DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.865095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff8fc27c-0378-462a-b836-fb3740e6f2fd · outbound

This paper cites P., and Yan, J.

A Theory for Compressibility of Graph Transformers for Transductive Learning P., and Yan, J

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.868519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64b8f0f2-adde-4ac1-a883-54605fe4aeea · outbound

This paper cites an unresolved cited work.

A Theory for Compressibility of Graph Transformers for Transductive Learning Unresolved cited work

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.872287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7589b553-6c72-457e-a1ea-30c121dff50b · outbound

This paper cites Do Transformers Really Perform Bad for Graph Representation?.

A Theory for Compressibility of Graph Transformers for Transductive Learning Do Transformers Really Perform Bad for Graph Representation?

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.875599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38212b63-321e-40c3-9dba-aef51f58b573 · outbound

This paper cites A., Ainslie, J., Alberti, C., Ontanon, S., Pham, P., Ravula, A., Wang, Q., Yang, L., et al.

A Theory for Compressibility of Graph Transformers for Transductive Learning A., Ainslie, J., Alberti, C., Ontanon, S., Pham, P., Ravula, A., Wang, Q., Yang, L., et al

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.879487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 5c315e0f-6257-48a1-936e-451c64faaca7 · inbound

Even Sparser Graph Transformers cites this paper.

Even Sparser Graph Transformers A Theory for Compressibility of Graph Transformers for Transductive Learning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T13:22:32.375169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31f77bde-ec7e-40cc-b9af-8444f9176e7d · inbound

TxPert: Leveraging Biochemical Relationships for Out-of-Distribution Transcriptomic Perturbation Prediction cites this paper.

TxPert: Leveraging Biochemical Relationships for Out-of-Distribution Transcriptomic Perturbation Prediction A Theory for Compressibility of Graph Transformers for Transductive Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T15:32:43.545613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88127997-c386-462f-8de5-662ba8b60a38 · inbound

SeedER: Seed-and-Expand Retrieval from Knowledge Graphs cites this paper.

SeedER: Seed-and-Expand Retrieval from Knowledge Graphs A Theory for Compressibility of Graph Transformers for Transductive Learning

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:55:23.299964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.