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Paper Citation Record · LEDGER

Recipe for a General, Powerful, Scalable Graph Transformer

As of 7 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T11:00:19.591474Z digest=sha256:ba03ecdb8e62154ac2be618679790457b82ffe4d172469f2ca9362a3e0696d3d

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:a048c08828f98bfa55afa2a84c994901744f5b7cfde42d1e37c8e76a8ab810b3

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:a22f0b53415b24505e5a74b6cf4a997edbbe89c61043f8b0a3f5efc1502ae9a2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T08:49:17.172538Z digest=sha256:326633d06b52eb33432d91d6b10815df3dbb81fbb82905d649abe798d52899ec

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T11:46:42.010486Z digest=sha256:58ccaa25b968ce11f2ff860ca548dec217cebf6298dee98a60c19e9ff8e88221

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T08:32:32.410473Z digest=sha256:52cffec3ce0630a44e039b12f3e5f94820b16303393b5194c6a0b7622714e7da

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T05:25:44.647620Z digest=sha256:571fbb2da6f7135483bf141736493839327e00a38e922137ecb046b53bcfe3a7

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-29T04:46:11.090693Z digest=sha256:c7f663e5bb047e8dc92241cee1fb444f86cf716236d753e9211739ef366d902c

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-07-03T22:41:41.912274Z digest=sha256:e416e09c0fb239fece89f817dc0780ddfbc4feaed774b31bf07585fda15b4f33

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=sha256:5a9b41b25a73fec54534dc21366e72f200966adc797df927f7491dba74e870c6

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=sha256:9f50d7151e04dc733b31107b09c9413034b7b11864c1793ade1a268711b597b0

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=sha256:8fbe8f90cb0da02890918490bedb5b1170c6f4d8f6823ca7161457d8e543981b

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=sha256:0f1c87d934ef02344486232424799b5e4c060dce59681de3ebb89d5cc7ff1f5d