Paper Citation Record · LEDGER

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

As of 22 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 11 inbound Pith citation observations for arXiv:2504.17323.

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

pith.paper-citation-record.v1
2504.17323 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:47:49.025716Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:36:17.347948Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T05:34:20.030150Z

Reference resolution

55 of 55 outbound references displayed

verified exact0
verified fuzzy49
unresolved5
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7b7d71dc-cd0d-4793-ade1-36733ef2f269 · outbound

This paper cites A tutorial on near -ﬁeld XL-MIMO communications towards 6G,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors A tutorial on near -ﬁeld XL-MIMO communications towards 6G,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.789423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9d741dea-0b29-4162-8d18-580cad32e198 · outbound

This paper cites A complete study o f space- time-frequency statistical properties of the 6G pervasive channel model,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors A complete study o f space- time-frequency statistical properties of the 6G pervasive channel model,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.779112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 67b4b9b8-f8f6-4197-bce6-75197a5c308b · outbound

This paper cites 6 G wireless channel measurements and models: Trends and chall enges,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors 6 G wireless channel measurements and models: Trends and chall enges,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.767702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7105869b-24b3-4c3d-a909-e6ab98d591f8 · outbound

This paper cites On th e road to 6G: Visions, requirements, key technologies, and te stbeds,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors On th e road to 6G: Visions, requirements, key technologies, and te stbeds,

Reference 4

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T10:47:49.756839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6ab584c6-9e6f-48a4-bf6f-ffeca11bbf43 · outbound

This paper cites Massive h ybrid antenna array for millimeter-wave cellular communication s,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Massive h ybrid antenna array for millimeter-wave cellular communication s,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.745433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 72841544-ddfd-4f44-a4d7-c0d33ffe3d8d · outbound

This paper cites Perv asive wireless channel modeling theory and applications to 6G GBS Ms for all frequency bands and all scenarios,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Perv asive wireless channel modeling theory and applications to 6G GBS Ms for all frequency bands and all scenarios,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.733954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a45b8bd9-6bfd-4bfe-b8cd-bee0ba4550fd · outbound

This paper cites Toward environment-aware 6G communic ations via channel knowledge map,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Toward environment-aware 6G communic ations via channel knowledge map,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.723016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 95941659-14e7-4a16-a434-a6e18db6304f · outbound

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

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors A tutorial on environment-aware communicati ons via channel knowledge map for 6G,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.711634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6f817dea-be8c-46dd-957f-ebf9b4e1d50d · outbound

This paper cites Environment-aware h ybrid beamforming by leveraging channel knowledge map,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Environment-aware h ybrid beamforming by leveraging channel knowledge map,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.699483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fbcfdf92-cfa4-462a-ac37-32eb36e030d1 · outbound

This paper cites Environment-aware ch annel estimation via integrating channel knowledge map and dynam ic sensing information,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Environment-aware ch annel estimation via integrating channel knowledge map and dynam ic sensing information,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.686005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 52ba953d-3c52-4a45-b4b3-281920521467 · outbound

This paper cites Environmen t-aware beam selection for IRS-aided communication with channel kn owledge map,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Environmen t-aware beam selection for IRS-aided communication with channel kn owledge map,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.673562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 633f0564-1304-40f3-a00e-8dbdaf4f5f39 · outbound

This paper cites CKM-Based environment-awar e pilot reuse and channel estimation,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors CKM-Based environment-awar e pilot reuse and channel estimation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.662350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7d376953-77f5-4d18-844f-1e1fbab9afaa · outbound

This paper cites CKM-Assisted LoS ide ntiﬁcation and predictive beamforming for cellular-connected UA V,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors CKM-Assisted LoS ide ntiﬁcation and predictive beamforming for cellular-connected UA V,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.650570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 015d0b57-37f7-4b45-bc02-191beba0e572 · outbound

This paper cites Prototyping and experimental results for environment-aw are millimeter wave beam alignment via channel knowledge map,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Prototyping and experimental results for environment-aw are millimeter wave beam alignment via channel knowledge map,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.639219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 16976317-3094-4e24-bbab-b9829c8c8b92 · outbound

This paper cites Environment-aware joint active/passive beamforming for RIS-aided communications leveraging channel knowledge map,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Environment-aware joint active/passive beamforming for RIS-aided communications leveraging channel knowledge map,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.628922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ecd22b63-b1a6-4398-b3a8-8680e001191e · outbound

This paper cites Channe l knowledge map (CKM)-assisted multi-UA V wireless network: CKM constr uction and UA V placement,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Channe l knowledge map (CKM)-assisted multi-UA V wireless network: CKM constr uction and UA V placement,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.617782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8df07e12-c00b-4a4a-bde2-bf7ab3479a71 · outbound

This paper cites Ca n channel knowledge map help to predict instantaneous MIMO ch annel state information?.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Ca n channel knowledge map help to predict instantaneous MIMO ch annel state information?

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.503785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bfbae128-80df-40b3-bbbc-9b8dd6f6464f · outbound

This paper cites Channel knowledge map aided channel prediction with measu rements- based evaluation,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Channel knowledge map aided channel prediction with measu rements- based evaluation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.492170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ce09c8ce-167e-4e6e-be06-bbbe2c0839f6 · outbound

This paper cites Interfe rence- cancellation-based channel knowledge map construction an d its applica- tions to channel estimation,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Interfe rence- cancellation-based channel knowledge map construction an d its applica- tions to channel estimation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.480466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8f02cd1d-c834-4e3f-a7b3-45a71a896d02 · outbound

This paper cites Fast tr ansmission control adaptation for URLLC via channel knowledge map and m eta- learning,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Fast tr ansmission control adaptation for URLLC via channel knowledge map and m eta- learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.469695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c4259c0c-4939-4619-9474-3d81561636d2 · outbound

This paper cites Channel map-based angle domain multiple acces s for cell- free massive MIMO communications,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Channel map-based angle domain multiple acces s for cell- free massive MIMO communications,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.458649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 65bd98e8-859c-4b51-86bf-4f0d75a73a0c · outbound

This paper cites Radio environment knowledge pool for 6G digital twin channel,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Radio environment knowledge pool for 6G digital twin channel,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.447417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5bb3f179-ae23-4c86-bb73-868567c6a506 · outbound

This paper cites Pr ototyping and experimental results for ISAC-based channel knowledge map,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Pr ototyping and experimental results for ISAC-based channel knowledge map,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.436160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7ae78c31-44a9-4d80-9f88-ccac71dff75b · outbound

This paper cites Environment-awar e wireless localization enabled by channel knowledge map,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Environment-awar e wireless localization enabled by channel knowledge map,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.423873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 261b11a1-c518-47c3-b765-b808a887ffd8 · outbound

This paper cites On the common A OA error in CKM-Based integrated sensing and communications,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors On the common A OA error in CKM-Based integrated sensing and communications,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.412184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 770b4a52-b931-45a8-b81f-4117254f6572 · outbound

This paper cites Channel knowledge map - enhanced clutter suppression for integrated sensing and co mmunication,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Channel knowledge map - enhanced clutter suppression for integrated sensing and co mmunication,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.400946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0138ed48-c1c5-45da-91a5-3228c3821c4b · outbound

This paper cites How much data is needed for channel kno wledge map construction?.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors How much data is needed for channel kno wledge map construction?

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.389396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 56cb78f4-4233-46ff-8257-03f1311194c9 · outbound

This paper cites Channel knowledge map fo r environment-aware communications: EM algorithm for map co nstruc- tion,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Channel knowledge map fo r environment-aware communications: EM algorithm for map co nstruc- tion,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.377937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 02c2c1d8-9a32-42ec-9324-3db6d0098ae3 · outbound

This paper cites K-nearest neighbor,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors K-nearest neighbor,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T10:47:48.927390Z

Source-reported events for the cited work

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Observation 1d185258-a0cd-41ef-a862-96a2a9a85574 · outbound

This paper cites Fixed rank Kriging for cellular coverage analysis,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Fixed rank Kriging for cellular coverage analysis,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.359017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c3861398-eb74-48ba-a58d-539ac6259e29 · outbound

This paper cites An adaptive inverse-distance we ighting spatial interpolation technique,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors An adaptive inverse-distance we ighting spatial interpolation technique,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.347132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 849df86a-4674-41bb-b642-799b5e00e14c · outbound

This paper cites Reducing the calibration effort fo r probabilistic indoor location estimation,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Reducing the calibration effort fo r probabilistic indoor location estimation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.335555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a0698091-ce43-425a-8489-152c85c55e97 · outbound

This paper cites An I2I inpa inting approach for efﬁcient channel knowledge map construction,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors An I2I inpa inting approach for efﬁcient channel knowledge map construction,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.323686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1f1acdd3-0906-4b0d-94b6-9c00971e162d · outbound

This paper cites Radiodiff: An effective generative diffusion model for sa mpling-free dynamic radio map construction,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Radiodiff: An effective generative diffusion model for sa mpling-free dynamic radio map construction,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.310614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6dc3bde2-8676-433d-b4ff-dc14d0e34497 · outbound

This paper cites IM Net: Interference-aware channel knowledge map construction an d localiza- tion,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors IM Net: Interference-aware channel knowledge map construction an d localiza- tion,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.297346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e0868e6f-4064-4b24-8713-ee59d2734555 · outbound

This paper cites Channel knowledge maps construction based on point cloud environment information ,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Channel knowledge maps construction based on point cloud environment information ,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.285170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8a399239-8a13-4d42-bf82-4a271bb4b36b · outbound

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

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors RadioUN et: Fast radio map estimation with convolutional neural networks,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.270993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2c78f948-014f-4aa0-ba08-81a451830372 · outbound

This paper cites RME-GAN: A learni ng framework for radio map estimation based on conditional gen erative adversarial network,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors RME-GAN: A learni ng framework for radio map estimation based on conditional gen erative adversarial network,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.259307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 06319b12-03da-43d8-b88b-297e0730de65 · outbound

This paper cites Denoising diffusion prob abilistic models,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Denoising diffusion prob abilistic models,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T10:47:48.964041Z

Source-reported events for the cited work

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Observation 3ad0c1e7-3b7d-44cc-82b1-783f2eb105e3 · outbound

This paper cites Dataset of Pathloss and ToA Radio Maps With Localization Application.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Dataset of Pathloss and ToA Radio Maps With Localization Application

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T10:47:48.967856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0e0c550-207c-42d2-a0a9-445cdab76457 · outbound

This paper cites CKMImageNet: A comprehensive dataset to enable channel knowledge map cons truction via computer vision,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors CKMImageNet: A comprehensive dataset to enable channel knowledge map cons truction via computer vision,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.240401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1bc11a15-8dad-45aa-8ef8-885e88568a8c · outbound

This paper cites Bilinear interpolat ion,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Bilinear interpolat ion,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.228759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 00de82c4-f975-4c64-9f2d-e0a73a2847f2 · outbound

This paper cites Kriging: a method of interp olation for geographical information systems,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Kriging: a method of interp olation for geographical information systems,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.217697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9665a8ea-2565-4c65-b917-d130feae4557 · outbound

This paper cites Diffusion models beat GANs o n image synthesis,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Diffusion models beat GANs o n image synthesis,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.204566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 492ecb18-c037-4e31-b927-47fe3a345e32 · outbound

This paper cites Improved techniques for training gans,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Improved techniques for training gans,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.193122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 838d01cb-f824-48d7-98c6-e31a66654662 · outbound

This paper cites High-resolution image synthesis with latent diffusion mo dels,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors High-resolution image synthesis with latent diffusion mo dels,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.182667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2683581c-44c0-40ec-94bc-b416ae79feaa · outbound

This paper cites Auto-encoding variational bayes,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Auto-encoding variational bayes,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.171707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7be7ea2f-6d1c-432f-887a-181971b2cc0b · outbound

This paper cites Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image Attenuation.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image Attenuation

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T10:47:48.997476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac8acf2f-8396-469d-9f01-90fc9bd204b9 · outbound

This paper cites Swin transformer: Hierarchical vision transforme r using shifted windows,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Swin transformer: Hierarchical vision transforme r using shifted windows,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.160481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3e2aa056-be07-4eca-899c-eedc75a82f37 · outbound

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

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Generative CKM Construction using Partially Observed Data with Diffusion Model

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-16T10:47:49.004898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77cba7b7-c1d4-408b-bd4a-dfc42e5d6c21 · outbound

This paper cites A computational approach to edge detection,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors A computational approach to edge detection,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.148211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c80116db-d007-4510-9191-be74fc172043 · outbound

This paper cites Wave propagation a nd radio network planning software winprop added to the electromagn etic solver package feko,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Wave propagation a nd radio network planning software winprop added to the electromagn etic solver package feko,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.136142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation da068977-6cb4-4dfe-ab61-a74d27e679d3 · outbound

This paper cites Image quality metrics: PSNR vs. SS IM,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Image quality metrics: PSNR vs. SS IM,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.122129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1226f379-ac48-48ef-9153-815c24459744 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a lo cal nash equilibrium,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Gans trained by a two time-scale update rule converge to a lo cal nash equilibrium,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.108164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b11faff2-ff5e-45ce-9ec7-d2ab3c72770b · outbound

This paper cites Conditional generative adve rsarial nets,.

CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors Conditional generative adve rsarial nets,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:47:49.095611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation 507a6501-0efd-4750-a84c-0b30a27d0192 · inbound

You May Use the Same Channel Knowledge Map for Environment-Aware NLoS Sensing and Communication cites this paper.

You May Use the Same Channel Knowledge Map for Environment-Aware NLoS Sensing and Communication CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-19T06:12:07.225524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8e1a8b88-864e-429c-8b67-7545e97eb174 · inbound

BS-1-to-N: Diffusion-Based Environment-Aware Cross-BS Channel Knowledge Map Generation for Cell-Free Networks cites this paper.

BS-1-to-N: Diffusion-Based Environment-Aware Cross-BS Channel Knowledge Map Generation for Cell-Free Networks CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T11:01:52.548644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68a0c827-61b2-454b-9f0a-8c6d40380040 · inbound

RadioMamba: Breaking the Accuracy-Efficiency Trade-off in Radio Map Construction via a Hybrid Mamba-UNet cites this paper.

RadioMamba: Breaking the Accuracy-Efficiency Trade-off in Radio Map Construction via a Hybrid Mamba-UNet CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T13:37:42.622222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb921094-025a-4074-8f5e-19d8bb13a08d · inbound

A Geometry Map-Based Site-Specific Propagation Channel Model for Urban Scenarios cites this paper.

A Geometry Map-Based Site-Specific Propagation Channel Model for Urban Scenarios CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:20:22.994973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 24424745-3d5e-463c-9281-9a963f24b2af · 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 CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-09T22:54:16.447614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6574a6e4-baf4-451b-a88a-9c944771abf9 · inbound

Towards Intelligent Low-Altitude Wireless Network Deployment: Differentiable Channel Knowledge Map Construction and Trajectory Design cites this paper.

Towards Intelligent Low-Altitude Wireless Network Deployment: Differentiable Channel Knowledge Map Construction and Trajectory Design CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:55:54.449621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1315bef1-7e28-4464-9ff2-fc39922f2df5 · inbound

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models cites this paper.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-30T05:34:20.032055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a2448248-b7cb-4989-b11c-1776a211c10e · inbound

Learning-Driven Channel Representation for Wireless Localization: From Channel Observations to Location Inference cites this paper.

Learning-Driven Channel Representation for Wireless Localization: From Channel Observations to Location Inference CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 146

Resolution: unresolved; no resolver link, observed 2026-08-02T00:42:12.492415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb3ebfe4-4b59-4747-9d85-47e0f2ea08f6 · inbound

RadioTrace: Transmitter-Aware Diffusion for Radio Map Estimation without Deployment-Time Fine-Tuning cites this paper.

RadioTrace: Transmitter-Aware Diffusion for Radio Map Estimation without Deployment-Time Fine-Tuning CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T15:36:17.347948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5d73fc4-0422-445f-8e05-97141b2dca31 · inbound

Construction and Dynamic Update of Channel Gain Maps via 3D Gaussian Splatting cites this paper.

Construction and Dynamic Update of Channel Gain Maps via 3D Gaussian Splatting CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T08:32:22.495754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c8701b0-2f64-46c0-a96d-d6d4dcdc5faa · inbound

Where to Perform Channel Measurements for CKM Construction: A Random Field Theory Analysis cites this paper.

Where to Perform Channel Measurements for CKM Construction: A Random Field Theory Analysis CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T19:16:32.764759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.