Paper Citation Record · LEDGER

Data-Driven Radio Propagation Modeling using Graph Neural Networks

As of 11 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2501.06236.

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

pith.paper-citation-record.v1
2501.06236 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:37:36.822970Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T00:15:17.328459Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T00:22:51.616137Z

Reference resolution

28 of 28 outbound references displayed

verified exact1
verified fuzzy10
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 196bd0fd-98ef-4510-a5bd-ed9f07927830 · outbound

This paper cites an unresolved cited work.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.533979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f4c7f27-73c0-4427-bb19-979bfe6958a5 · outbound

This paper cites Adewole, Abubakar Ab- dulkarim, Abdulkarim A.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Adewole, Abubakar Ab- dulkarim, Abdulkarim A

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:38.339610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7ccba7d8-0f2f-4cb4-a0eb-b1ec43a0e2de · outbound

This paper cites Bakirtzis, J.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Bakirtzis, J

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.561231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17c02f93-7f70-435c-86b6-596312b6236c · outbound

This paper cites an unresolved cited work.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:37:38.304348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2a4f6600-1126-4f3f-9d36-491152b4bf44 · outbound

This paper cites Eller, P.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Eller, P

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.576391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8806add2-fd0f-44d4-afc6-e3eb053e1754 · outbound

This paper cites Kitao, and M.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Kitao, and M

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:38.267958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 94471c09-12a1-4448-8e63-8bb7a6ed5368 · outbound

This paper cites ”State-of-the-art in artificial neural network applications: A survey.” Heliyon 4.11 (2018): e00938.

Data-Driven Radio Propagation Modeling using Graph Neural Networks ”State-of-the-art in artificial neural network applications: A survey.” Heliyon 4.11 (2018): e00938

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:38.230042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 89049d37-7a2b-43eb-beab-7bc68ad9c7a9 · outbound

This paper cites An introduction to neural networks.

Data-Driven Radio Propagation Modeling using Graph Neural Networks An introduction to neural networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:38.181083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 84e02e7a-1ea0-4c79-97a3-d6a82dc7f301 · outbound

This paper cites Learning Mesh-Based Simulation with Graph Networks.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Learning Mesh-Based Simulation with Graph Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.615934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d967eeb-293b-4fb7-bae7-dce9e6e5369a · outbound

This paper cites ”Neural message passing for quantum chemistry.” International conference on machine learning.

Data-Driven Radio Propagation Modeling using Graph Neural Networks ”Neural message passing for quantum chemistry.” International conference on machine learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:38.142636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 23d3d5d8-4d10-4b8c-b4cc-0073a0a8f476 · outbound

This paper cites ”Graph networks as learnable physics engines for inference and control.” International Conference on Machine Learning.

Data-Driven Radio Propagation Modeling using Graph Neural Networks ”Graph networks as learnable physics engines for inference and control.” International Conference on Machine Learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:38.110751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 060ee899-fc24-4205-992b-2f59607f7eb6 · outbound

This paper cites Iskander.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Iskander

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:38.062897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 58284f68-f32b-4c3f-b158-8d8a15537e7a · outbound

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

Data-Driven Radio Propagation Modeling using Graph Neural Networks Semi-Supervised Classification with Graph Convolutional Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.659995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23618f1a-454e-49c2-9af3-da21f3711c3d · outbound

This paper cites an unresolved cited work.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:37:38.037315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8e5f1d57-1349-4690-ad39-8eda16b41e6e · outbound

This paper cites an unresolved cited work.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:37:37.996545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8b03473d-bff2-4357-95cc-639ba012ae93 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Fourier Neural Operator for Parametric Partial Differential Equations

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.684556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eab34db0-413d-4c61-9c9f-dedbc58ac985 · outbound

This paper cites Vision GNN: An Image is Worth Graph of Nodes.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Vision GNN: An Image is Worth Graph of Nodes

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.700211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7eb3af09-e486-4505-a6ab-e3fc0bce9424 · outbound

This paper cites (2018, April).

Data-Driven Radio Propagation Modeling using Graph Neural Networks (2018, April)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:37.955904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e59e55b9-075f-4814-9c24-fe9e8d5d73df · outbound

This paper cites Conditioned-U-Net: Introducing a Control Mechanism in the U-Net for Multiple Source Separations.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Conditioned-U-Net: Introducing a Control Mechanism in the U-Net for Multiple Source Separations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.720063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb26cdf1-b001-4223-9872-724a2bedc233 · outbound

This paper cites et al., 2019.

Data-Driven Radio Propagation Modeling using Graph Neural Networks et al., 2019

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:37.919612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e606a407-694f-4a49-84b2-99c0d30d7137 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Fast Graph Representation Learning with PyTorch Geometric

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.751673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60314189-1026-4b55-83dc-79641b50c739 · outbound

This paper cites Using AntiPatterns to avoid MLOps Mistakes.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Using AntiPatterns to avoid MLOps Mistakes

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:37:37.112548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f27df910-62d0-4504-8c6b-5396e0f9eb87 · outbound

This paper cites an unresolved cited work.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:37:37.893648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 094289c8-9188-4f9b-8cd6-de3b41371e8a · outbound

This paper cites an unresolved cited work.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:37:37.871782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5934cfe7-3daa-42b8-afcc-77daa39d48ad · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Adam: A Method for Stochastic Optimization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.792833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8cac0c1-80ee-403d-bf8a-8a871c09ba41 · outbound

This paper cites Conditional Generative Adversarial Nets.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Conditional Generative Adversarial Nets

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.801288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 374dc1bc-143d-4320-99e9-dc4f31dea2c4 · outbound

This paper cites J., Gruber, M.

Data-Driven Radio Propagation Modeling using Graph Neural Networks J., Gruber, M

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:37:37.841488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 13598ba1-6b99-4c51-84b9-15f016da96d4 · outbound

This paper cites Graph Attention Networks.

Data-Driven Radio Propagation Modeling using Graph Neural Networks Graph Attention Networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:36.822970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation fd22f339-3e94-45af-bdf0-25db837a746b · inbound

From Waves to Graphs: A Ray-Tracing-Inspired Neural Radio Propagation Model cites this paper.

From Waves to Graphs: A Ray-Tracing-Inspired Neural Radio Propagation Model Data-Driven Radio Propagation Modeling using Graph Neural Networks

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.617743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.