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Paper Citation Record · LEDGER

Recipe for a General, Powerful, Scalable Graph Transformer

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2205.12454.

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

pith.paper-citation-record.v1
2205.12454 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:39:46.317375Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T22:49:01.144766Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a905d530-e73f-4cc5-aaf7-f0e28ff1c434 · inbound

Explaining the Explainers in Graph Neural Networks: a Comparative Study cites this paper.

Explaining the Explainers in Graph Neural Networks: a Comparative Study Recipe for a General, Powerful, Scalable Graph Transformer

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-05-24T11:04:22.271951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-24T11:00:19.591474Z digest=sha256:132436f9998345a7316519a8505b2f1d49821d0ac2df18d40a3c6de8fd63ffb6

Observation e7967d9c-7540-4455-b4eb-0372a664a8f7 · inbound

TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows cites this paper.

TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows Recipe for a General, Powerful, Scalable Graph Transformer

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-05T23:39:46.317375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:39:46.317375Z digest=sha256:2f1550774a4d01e8872b0fb499a9af6fb4b1953979722ea626ed34fdd1b470e9

Observation 9b4d8adf-070c-4cfd-9a2d-b5e2bd235868 · inbound

GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Framework cites this paper.

GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Framework Recipe for a General, Powerful, Scalable Graph Transformer

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-05T13:36:41.294250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:36:41.294250Z digest=sha256:6a76b645d362f6e940bf9bfd480296a38ce6205f735b8a3cfb3d7a8d4d815fe1

Observation e3d3586a-25d8-4370-b548-05fb84db9f25 · inbound

Towards Generalization of Graph Neural Networks for AC Optimal Power Flow cites this paper.

Towards Generalization of Graph Neural Networks for AC Optimal Power Flow Recipe for a General, Powerful, Scalable Graph Transformer

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-18T08:51:08.879177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T08:49:17.172538Z digest=sha256:e8aa234f03efc03d3cd2df12653ad93eba888c904162e97dae2e8f6cb34d8793

Observation 71435054-b894-4f93-8153-55e6b4d549ed · inbound

GCCM: Enhancing Generative Graph Prediction via Contrastive Consistency Model cites this paper.

GCCM: Enhancing Generative Graph Prediction via Contrastive Consistency Model Recipe for a General, Powerful, Scalable Graph Transformer

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:31:08.902554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T11:46:42.010486Z digest=sha256:8ce976eb3458dc1c8cebb4f2699a4793d32146427b02522129b7b1c693fd4ec1

Observation cc66436f-a3ef-4258-bcf1-7ef5ef6fc516 · inbound

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification cites this paper.

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification Recipe for a General, Powerful, Scalable Graph Transformer

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-21T08:34:05.427421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T08:32:32.410473Z digest=sha256:7421ab58a40ec7e4877a4d0f1dcd02020344e5f5aec745ba9b3b5db1dcda3e10

Observation 90872906-c477-402a-a0ab-be8017ac96ed · inbound

COAgents: Multi-Agent Framework to Learn and Navigate Routing Problems Search Space cites this paper.

COAgents: Multi-Agent Framework to Learn and Navigate Routing Problems Search Space Recipe for a General, Powerful, Scalable Graph Transformer

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T05:29:39.689101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T05:25:44.647620Z digest=sha256:f96b611afe6d7607e1c5ce9606a0b7e8aef6f04553dc7c2930c023a79478ee0f

Observation 132dc31b-ed18-4b92-94c9-17f771cd6df2 · inbound

Agent vs. Parametric World Models: Hybrid Planning for Reliable Language Agents cites this paper.

Agent vs. Parametric World Models: Hybrid Planning for Reliable Language Agents Recipe for a General, Powerful, Scalable Graph Transformer

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T19:23:54.334687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-29T04:46:11.090693Z digest=sha256:e24016635e439c3a021b630abe0bb8ef9d00766a582c9fade5118c7b92227735

Observation 0a446ed8-1796-4123-96e6-b84740aa46a8 · inbound

Agent vs. Parametric World Models: Hybrid Planning for Reliable Language Agents cites this paper.

Agent vs. Parametric World Models: Hybrid Planning for Reliable Language Agents Recipe for a General, Powerful, Scalable Graph Transformer

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T22:49:01.147535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-03T22:41:41.912274Z digest=sha256:a6a11f629570ec0116d3a3af0f860553d7677aa7470010a34d682e4055d1c39c

Observation e60150f2-2da1-4eaf-8249-ff92e9fc0a4f · inbound

A Computational Ethical Framework for Financial Digital Phenotyping for Mental Health cites this paper.

A Computational Ethical Framework for Financial Digital Phenotyping for Mental Health Recipe for a General, Powerful, Scalable Graph Transformer

Reference 138

Resolution
unresolved
no resolver link, observed 2026-07-31T19:30:13.419111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T19:30:13.419111Z digest=sha256:f3c1495ae1c68ed96262ac7c481c8994a4badd52cf1cde4facb6d42d73b09085

Observation 04e3fa1c-35f0-4102-a681-4e4302d6142a · inbound

Schreier-Coset Graph Rewiring cites this paper.

Schreier-Coset Graph Rewiring Recipe for a General, Powerful, Scalable Graph Transformer

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-01T07:18:40.951654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:18:40.951654Z digest=sha256:0123c523d3acce6b5e8326918c895983c58fbd0328e2c0ce1ef64b5f31ed2f27

Observation 3d6d7a73-a994-4844-8a91-7449647dfadc · inbound

Learning to Trace Seiberg Dualities cites this paper.

Learning to Trace Seiberg Dualities Recipe for a General, Powerful, Scalable Graph Transformer

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-31T01:45:49.847838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T01:45:49.847838Z digest=sha256:e62b86690708e36710b9a16308de77f1df9447a7ecbee8f216ab405596b57fd7

Observation 41a7a1f5-207c-4345-b39a-83f65bb5a417 · inbound

Benchmarking Sheaf Neural Networks for Inductive Tasks cites this paper.

Benchmarking Sheaf Neural Networks for Inductive Tasks Recipe for a General, Powerful, Scalable Graph Transformer

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-04T04:52:32.459395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:52:32.459395Z digest=sha256:f14ce93a892f2e0d1d8306f1d6bf723b44fa20cacf2b44418ae513baeecab983