Pith. sign in

Paper Citation Record · LEDGER

RMTransformer: Accurate Radio Map Construction and Coverage Prediction

As of 19 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2501.05190.

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

pith.paper-citation-record.v1
2501.05190 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:16:36.296228Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T22:50:38.406996Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-09T22:54:16.443935Z

Reference resolution

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy22
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e8e9e14a-12e5-4ef6-89c5-3819dfa01f15 · outbound

This paper cites When AI meets sustainable 6G,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction When AI meets sustainable 6G,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.898339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.144251Z digest=sha256:c5abdb898b883c414ec35e8953ee21b07c8db8b71eac9b6cec49301cd215b770

Observation 6e3e5f22-5633-4d35-bc0f-53b6b4cc4ac4 · outbound

This paper cites Digital twins for next-generation mobile networks: Appli- cations and solutions,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Digital twins for next-generation mobile networks: Appli- cations and solutions,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.879160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.150381Z digest=sha256:fb28dd4918f310302408b1ca50f57417d22dc25d86e47a36b722003cbaf0c32e

Observation 619217a9-1b0d-4b83-9ff2-04ff5526e3cf · outbound

This paper cites Digital twins from a networking perspective,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Digital twins from a networking perspective,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.855375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.157052Z digest=sha256:b1ac4b47e84d138ea414a1f249f888c0b61df5715e48e7fbeff5af9bfb7c86b0

Observation 835754dc-6314-474c-808f-9daf43806f04 · outbound

This paper cites Digital twin-aided learning to enable robust beamforming: Limited feedback meets deep generative models,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Digital twin-aided learning to enable robust beamforming: Limited feedback meets deep generative models,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.836458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.162987Z digest=sha256:7f4589892baced1074ca6e3ff0b64ee037c8a34f2f02d167e600062e2055612e

Observation c7e62717-16f9-40bf-b73b-bd6a40ab5d8e · outbound

This paper cites Optimization of broadcast beams in massive MIMO: Learning from a digital twin,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Optimization of broadcast beams in massive MIMO: Learning from a digital twin,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.809606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.169918Z digest=sha256:9ad3a5811038f8c6129ff70ee3bad2366ca7f32177c22efc2e8deac840948e54

Observation 193081fc-c0ea-4e4f-b715-a04f2dd79d65 · outbound

This paper cites Generative learning-powered probing beam optimization for cell-free hybrid beamforming,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Generative learning-powered probing beam optimization for cell-free hybrid beamforming,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.785396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.175890Z digest=sha256:ab713ff17e126e50c72adf47ec8a1fc005cbfd6e07226e67f7bb6e20beff9626

Observation 9817ff16-d448-4a5b-b68f-ead4bc7b09ee · outbound

This paper cites Locunet: Fast urban positioning using radio maps and deep learning,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Locunet: Fast urban positioning using radio maps and deep learning,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.758043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.182091Z digest=sha256:9cb61a563c5d147f238389bfb47886a5fce24ca0fc2560e5766ef914ff1ed88f

Observation 996088c5-44f8-44be-9449-1e31014ad877 · outbound

This paper cites Digital twin-enhanced deep reinforcement learning for resource management in networks slicing,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Digital twin-enhanced deep reinforcement learning for resource management in networks slicing,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.737975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.187517Z digest=sha256:0fed626870ba8c46f0df3257ca79aea7b5d094a039ded847a64b3688e7b10017

Observation ad0cc76a-41b0-4f9f-af1a-06f9ca44053f · outbound

This paper cites Pathloss prediction using deep learning with applications to cellular optimization and efficient D2D link scheduling,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Pathloss prediction using deep learning with applications to cellular optimization and efficient D2D link scheduling,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.709429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.192865Z digest=sha256:62b78ba1897a9001cf9099b124d925de194c34120ed31fef604c9664083fa842

Observation eb8034d1-0d74-4f02-9f9e-ad643eb44c4d · outbound

This paper cites Dominant path prediction model for urban scenarios,,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Dominant path prediction model for urban scenarios,,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.680961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.198420Z digest=sha256:1b16f2c7a3ad27392dbb98764b394b5402260508f9e3b599afed4ffa3da6eb52

Observation ead00331-575f-4319-9048-9ce3ef2ba3c8 · outbound

This paper cites Real-time digital twins: Vision and research directions for 6G and beyond,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Real-time digital twins: Vision and research directions for 6G and beyond,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.660820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.203510Z digest=sha256:63b1a8c25dbce4df55b246d1b2a42926e0342ca0c5976f941372f47eb70e9df7

Observation 481fa20c-41df-42df-b054-14f7b008b542 · outbound

This paper cites ML-assisted beam selection via digital twins for time-sensitive indus- trial IoT,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction ML-assisted beam selection via digital twins for time-sensitive indus- trial IoT,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.634820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.208676Z digest=sha256:8e6532a7a5a0fee8f16e760abf9deef7ce345c5b2e52bae1a207e34d56a79025

Observation 3fcb2ee9-3052-4f97-93f7-0421c7a52fef · outbound

This paper cites Radio map estimation: A data-driven approach to spectrum cartography,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Radio map estimation: A data-driven approach to spectrum cartography,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.604006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.215732Z digest=sha256:3deefe1b259af79bb7069403a4cd1764baa452e4c90d5b7d1355f5e658bb3357

Observation ceb3728b-6906-426b-b4a3-2759cb29583f · outbound

This paper cites WiNeRT: Towards neural ray tracing for wireless channel modelling and differentiable simulations,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction WiNeRT: Towards neural ray tracing for wireless channel modelling and differentiable simulations,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.581310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.222468Z digest=sha256:7c934775fc63d4837a1c89819f0bf285d4d91ab4cc2affa09e1b74c94bdf8545

Observation b4bcf623-c9ba-4756-a7a9-4a44b25f8295 · outbound

This paper cites NeRF2: Neural radio-frequency radiance fields,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction NeRF2: Neural radio-frequency radiance fields,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.557040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.230616Z digest=sha256:76d255ec685e4bf915d8850dfa75af14a2772de986ac111b7feaa7ef153af9e9

Observation 12cd2c4e-d43d-4340-8156-cb9d9743ca6c · outbound

This paper cites Neural Representation for Wireless Radiation Field Reconstruction: A 3D Gaussian Splatting Approach.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Neural Representation for Wireless Radiation Field Reconstruction: A 3D Gaussian Splatting Approach

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T21:16:36.238118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:16:36.238118Z digest=sha256:9fb1d062aad165f949a9ec6902cef87a55a717a4e27c6ad98dcea4f02b58aa50

Observation f63da909-ecaf-4493-9995-879afc67bae0 · outbound

This paper cites Study on channel model for frequencies from 0.5 to 100 GHz,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Study on channel model for frequencies from 0.5 to 100 GHz,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.526751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.247424Z digest=sha256:916f8c92d68140da37d339ffdfac5f64500e8edd000fd89ef037981e6bdc91f6

Observation 09fef730-7b5b-489c-bf22-08191f5c8349 · outbound

This paper cites Radiounet: Fast radio map estimation with convolutional neural networks,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction Radiounet: Fast radio map estimation with convolutional neural networks,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.500232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.254535Z digest=sha256:14a5d8c156a53d73c126d12d92f288b1ce7bb0968a0a94cd7a7d0b8e6c25b8e9

Observation 69824261-fca5-449a-83a2-0c0a268724af · outbound

This paper cites PMNet: Large-scale channel prediction system for ICASSP 2023 first pathloss radio map prediction challenge,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction PMNet: Large-scale channel prediction system for ICASSP 2023 first pathloss radio map prediction challenge,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.473830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.263799Z digest=sha256:2cf68b61ba7754bee37e12488d531f1f283d9aa481a47dce53162f67b167c086

Observation 9b642dfe-ff63-43ec-8672-15b471af9dc9 · outbound

This paper cites A scalable and generalizable pathloss map prediction,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction A scalable and generalizable pathloss map prediction,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.451169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.274815Z digest=sha256:3b12dd7bbf33fe658e5a0b1231964bc56308432e370eb5bc2d98956268594adc

Observation 5aefc334-3894-4f5d-88f6-1cee13452b07 · outbound

This paper cites The first pathloss radio map prediction challenge,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction The first pathloss radio map prediction challenge,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.423500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.285701Z digest=sha256:7773a34dddfe8a771ff25f0c97599d9f6ff5dc277f01e4042a23ba1ed877b187

Observation b05c26f2-f581-4077-99e0-4eb4d6097afd · outbound

This paper cites MaxViT: Multi-axis vision transformer,.

RMTransformer: Accurate Radio Map Construction and Coverage Prediction MaxViT: Multi-axis vision transformer,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.398282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.290891Z digest=sha256:68b66b981de48f4c889a8bbcd9d298fc76d2926ab063076ace7985ff0b3db7ec

Observation ee67def7-6dcf-465b-8a0b-31b7006ce236 · outbound

This paper cites [Online].

RMTransformer: Accurate Radio Map Construction and Coverage Prediction [Online]

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:16:36.377066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:16:36.296228Z digest=sha256:6c0aea59f2afb10a22c52a5ff72b3c854c41dc0e165d8bb58688692fdbc54e4a

Pith citing papers

Observation 074cbe05-5994-4aed-97cf-d054c31c090c · inbound

CKM Beyond Channel Gain: Spatial Correlation Map Construction with Deep Learning cites this paper.

CKM Beyond Channel Gain: Spatial Correlation Map Construction with Deep Learning RMTransformer: Accurate Radio Map Construction and Coverage Prediction

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-09T22:54:16.445203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-09T22:50:38.406996Z digest=sha256:9f8ca6c36cb8553b4bd615ad3243011f86ed0a4e6398b3e9ad429572a1c486b9