Paper Citation Record · LEDGER

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion

As of 17 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2607.01777.

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

pith.paper-citation-record.v1
2607.01777 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-03T08:08:44.550698Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

34 of 34 outbound references displayed

verified exact4
verified fuzzy30
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2854f38f-bc2b-4706-a86c-890012c817e5 · outbound

This paper cites PINN and GNN- based RF map construction for wireless communication systems,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion PINN and GNN- based RF map construction for wireless communication systems,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.932786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 347e427c-11e8-495e-abcc-7bab9560b277 · outbound

This paper cites A survey on beyond 5G network slicing for smart cities applications,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion A survey on beyond 5G network slicing for smart cities applications,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.908238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 90edffbb-5e15-4e26-b118-3b5e716832a0 · outbound

This paper cites A tutorial on extremely large-scale MIMO for 6G: Fundamentals, signal processing, and applications,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion A tutorial on extremely large-scale MIMO for 6G: Fundamentals, signal processing, and applications,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.958984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1beea28b-bd68-4e58-b198-00605f580881 · outbound

This paper cites Satellite- terrestrial integrated 6G: An ultra-dense LEO networking management architecture,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Satellite- terrestrial integrated 6G: An ultra-dense LEO networking management architecture,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.917545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 050cfea7-6806-4aa8-bad3-9f72af7e77cb · outbound

This paper cites A comprehensive survey of knowledge-driven deep learning for intelligent wireless network optimization in 6G,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion A comprehensive survey of knowledge-driven deep learning for intelligent wireless network optimization in 6G,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.939677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dcb1bda1-3a53-490d-bc05-e262f836f733 · outbound

This paper cites A tutorial on environment-aware communications via channel knowledge map for 6G,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion A tutorial on environment-aware communications via channel knowledge map for 6G,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.956617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 59767ae4-32c0-426c-97d0-8e26528b0315 · outbound

This paper cites Field strength and its variability in VHF and UHF land- mobile radio service,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Field strength and its variability in VHF and UHF land- mobile radio service,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.961430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6d1603ac-1849-44ec-b69d-fa580eb09976 · outbound

This paper cites Empirical formula for propagation loss in land mobile radio services,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Empirical formula for propagation loss in land mobile radio services,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.959220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7607a99e-c705-4c49-835d-1d3d6afedb41 · outbound

This paper cites 3GPP TR38.901,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion 3GPP TR38.901,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.966550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 70e92e4a-4588-4980-a3a1-f6501a3695b0 · outbound

This paper cites Two-dimensional ray-tracing modeling for propagation prediction in microcellular environments,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Two-dimensional ray-tracing modeling for propagation prediction in microcellular environments,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.931326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dfedfd3a-1476-4c08-a5f6-1ae19d3a8037 · outbound

This paper cites Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:17:44.905559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 81b755c8-1339-4809-97d6-30c575adba00 · outbound

This paper cites Channel gain map tracking via distributed Kriging,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Channel gain map tracking via distributed Kriging,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.930597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a067dd90-473c-4c36-a0a9-13cfef5c8235 · outbound

This paper cites Tensor completion for radio map reconstruction using low rank and smoothness,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Tensor completion for radio map reconstruction using low rank and smoothness,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.965313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b8901ad4-4c13-4ac3-a1fa-4be7cf40ee10 · outbound

This paper cites A method to reconstruct coverage loss maps based on matrix completion and adaptive sampling,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion A method to reconstruct coverage loss maps based on matrix completion and adaptive sampling,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.900955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 931857f7-5f74-4099-9b5f-3773c5de6ffa · outbound

This paper cites RadioUNet: fast radio map estimation with convolutional neural networks,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion RadioUNet: fast radio map estimation with convolutional neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.936152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a484ac6f-039a-433d-8eab-0e5e6e7bfd06 · outbound

This paper cites Geo2SigMap: High-fidelity RF signal mapping using geographic databases,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Geo2SigMap: High-fidelity RF signal mapping using geographic databases,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.922714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9584f6d6-2419-41c5-8ca1-6dd8edeeea93 · outbound

This paper cites A graph neural network based radio map construction method for urban environment.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion A graph neural network based radio map construction method for urban environment

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.970149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9049efcf-ed6d-4b3e-b4f9-f616b37c130f · outbound

This paper cites RME-GAN: A learning framework for radio map estimation based on conditional generative adversarial network.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion RME-GAN: A learning framework for radio map estimation based on conditional generative adversarial network

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.950389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fcae7ac7-4982-4d6b-bd7a-36ce287e6ad9 · outbound

This paper cites ACT-GAN: Radio map construction based on generative adversarial networks with ACT blocks,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion ACT-GAN: Radio map construction based on generative adversarial networks with ACT blocks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.954766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a4c01692-5657-402d-a3b8-1abfaff3d26f · outbound

This paper cites RecuGAN: A novel generative AI approach for synthesizing RF coverage maps,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion RecuGAN: A novel generative AI approach for synthesizing RF coverage maps,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.971123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5ea93de4-ec98-479b-b608-c45dd68a4705 · outbound

This paper cites RadioDiff: An effective generative diffusion model for sampling-free dynamic radio map construction,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion RadioDiff: An effective generative diffusion model for sampling-free dynamic radio map construction,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.937512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 51f98dbd-f55b-4f5a-b4df-48bc3be7894b · outbound

This paper cites RadioDiff-3D: A 3D×3D radio map dataset and generative diffusion based benchmark for 6G environment-aware com- munication,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion RadioDiff-3D: A 3D×3D radio map dataset and generative diffusion based benchmark for 6G environment-aware com- munication,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.945671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cbe54039-e336-4bfc-a613-3c6b46e5bfea · outbound

This paper cites Generative CKM Construction using Partially Observed Data with Diffusion Model.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Generative CKM Construction using Partially Observed Data with Diffusion Model

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:17:44.911402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7ba2c78f-16be-42ef-a3ff-814ca79832c1 · outbound

This paper cites Beamckmdiff: Beam- aware channel knowledge map construction via diffusion transformer.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Beamckmdiff: Beam- aware channel knowledge map construction via diffusion transformer

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:17:44.908571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b78cd4e7-0300-4226-b0ec-1492c3c0c686 · outbound

This paper cites CKMImageNet: A dataset for AI-based channel knowledge map toward environment-aware communication and sensing,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion CKMImageNet: A dataset for AI-based channel knowledge map toward environment-aware communication and sensing,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.952693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 01e6fdbf-479f-48b6-93aa-99a082d7e399 · outbound

This paper cites Deep machine learning-based AoD map and AoA map construction for wireless networks,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Deep machine learning-based AoD map and AoA map construction for wireless networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.954581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1c6dd49f-82dc-4143-935e-28a8880a1120 · outbound

This paper cites Indoor environment learning via RF-mapping,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Indoor environment learning via RF-mapping,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.963426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 61f38cbd-b360-4f0e-90f1-ee8cf6b0d7ed · outbound

This paper cites Physics-informed machine learning,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Physics-informed machine learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.964275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9fb5913d-b9c4-4535-a8a9-87af07cc85cb · outbound

This paper cites Physics-informed generalizable wireless channel modeling with segmentation and deep learning: Fundamentals, methodologies, and challenges,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Physics-informed generalizable wireless channel modeling with segmentation and deep learning: Fundamentals, methodologies, and challenges,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.972577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 89d95545-ecf9-4092-a943-557d21d2ff13 · outbound

This paper cites The graph neural network model,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion The graph neural network model,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.935086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b508f3b3-7ed0-4bcd-8acf-0d5bcce14ea6 · outbound

This paper cites Inductive representation learning on large graphs,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Inductive representation learning on large graphs,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.952490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation da58dd81-0fd7-4f6d-bb27-e8722d9e39c5 · outbound

This paper cites Wave propagation and radio network planning software WinProp added to the electromagnetic solver package FEKO,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion Wave propagation and radio network planning software WinProp added to the electromagnetic solver package FEKO,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.973140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ef93979c-b720-44c0-beb0-79bba87109e9 · outbound

This paper cites OpenPathNet: An open-source RF multipath data generator for AI-driven wireless systems.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion OpenPathNet: An open-source RF multipath data generator for AI-driven wireless systems

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:17:44.914203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 231adb37-54f4-4d4c-9b68-a55be31b38c0 · outbound

This paper cites DeepMIMO: A generic deep learning dataset for mil- limeter wave and massive MIMO applications,.

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion DeepMIMO: A generic deep learning dataset for mil- limeter wave and massive MIMO applications,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T11:10:55.920109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.