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Paper Citation Record · LEDGER

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication

As of 10 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 1 inbound Pith citation observation for arXiv:2507.12166.

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

pith.paper-citation-record.v1
2507.12166 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:57:35.540874Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T05:09:07.754702Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T10:16:52.301257Z

Reference resolution

69 of 69 outbound references displayed

  • verified exact0
  • verified fuzzy56
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 232dcd7d-41e3-4035-9d23-e7a4690ff36f · outbound

This paper cites 6G omni-scenario on-demand services provisioning: vision, technology and prospect(in chinese),.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication 6G omni-scenario on-demand services provisioning: vision, technology and prospect(in chinese),

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.360378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.190207Z digest=sha256:66b660ce389874c21cea5e22debe30e31320670842640af8b28eec8792bd9c46

Observation 1a342411-2242-40a8-9c56-3858183498de · outbound

This paper cites Toward immersive communications in 6G,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Toward immersive communications in 6G,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.351967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.243200Z digest=sha256:fb4aceb40c2a023a1e6e5c22ddc63ac97b45b2063c81bfa7a973585b79247162

Observation 6b8d2006-a306-4620-8850-ce2705595e3c · outbound

This paper cites Federated learning empowered computation offloading and resource management in 6g-v2x,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Federated learning empowered computation offloading and resource management in 6g-v2x,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.343312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.351230Z digest=sha256:52d9a5a36dcd885cbb8befd6f3e4d93216f8df68d2df50ac632b66aa36844e95

Observation cb91dc62-60a8-4085-993a-24a3b88117bc · outbound

This paper cites Deep learning-powered vessel trajectory prediction for improving smart traffic services in maritime internet of things,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Deep learning-powered vessel trajectory prediction for improving smart traffic services in maritime internet of things,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.334360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.430311Z digest=sha256:433451e01a1b1fe9ad2c4cc747c5112ac9db154b70be73d20f0e37e62d8812a1

Observation 67317ddb-3f6a-433c-b34b-09441734045a · outbound

This paper cites Channel estimation for extremely large-scale massive mimo systems,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Channel estimation for extremely large-scale massive mimo systems,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.325488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.532439Z digest=sha256:ed2e2a7afb036417c8a24301ccafa9e1d78569aeb7188cc324737d3be8d7e240

Observation f82eaedb-5ac3-4002-8384-aff3500c38c6 · outbound

This paper cites Federated learning in massive mimo 6g networks: Convergence analysis and communication-efficient design,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Federated learning in massive mimo 6g networks: Convergence analysis and communication-efficient design,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.315808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.646243Z digest=sha256:1d231845201b58be3e1c803fc4b21bf244c2b995f2f82ef3afb647efaea0e94b

Observation 5b0c4b96-83bd-4b0a-a833-0ed03ae7f224 · outbound

This paper cites Channel state information prediction for 5g wireless communications: A deep learning approach,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Channel state information prediction for 5g wireless communications: A deep learning approach,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.307185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.753209Z digest=sha256:76d51893a525444963f13285b14ec26e8c6e5e4a70cb6625285974dd837fdb01

Observation 8d18268d-41ce-455c-9c98-f56ca99b5b39 · outbound

This paper cites Ultra dense satellite-enabled 6G networks: Resource optimization and interference management,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Ultra dense satellite-enabled 6G networks: Resource optimization and interference management,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.297437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.827465Z digest=sha256:391d005ba4abd4079576aea11b5b37f9450c52d1517fb471d57a9fc94bf06543

Observation 8f593f45-d36e-47f3-8b6e-7ea0d56c6564 · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication A tutorial on extremely large-scale MIMO for 6G: Fundamentals, signal processing, and applications,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.288022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.900760Z digest=sha256:e85a634257e8f2c54efece79168f3d168d9a5b4280d3ea2ec5d95fce8fc1174e

Observation 3a21e404-6140-463b-969e-7dc5f33e0bef · outbound

This paper cites Learning in the air: Secure federated learning for uav-assisted crowdsensing,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Learning in the air: Secure federated learning for uav-assisted crowdsensing,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.278673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:28.998911Z digest=sha256:b3910f08bdffe76bc11f40e46c4dde39ca13bc59aaa5636cacfe1d445d6b4bbe

Observation 1f5fd1f4-c9f4-40ac-96be-82e6319a9a0e · outbound

This paper cites Intelligent ubiquitous network accessibility for wireless-powered mec in uav- assisted b5g,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Intelligent ubiquitous network accessibility for wireless-powered mec in uav- assisted b5g,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.269784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:29.072651Z digest=sha256:17f8ff061fd013d988f96752fca950f5af22ed8883f18d09758b1c9580d9f6dc

Observation abe20dd6-c976-4f0b-802a-b26a55400840 · outbound

This paper cites Bd-vte: A novel baseline data based verifiable trust evaluation scheme for smart network systems,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Bd-vte: A novel baseline data based verifiable trust evaluation scheme for smart network systems,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.260310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:29.141297Z digest=sha256:210e090c5312ddb8371e9fb668f9a512a24b20ff700324b64a0da9cc81a10ed0

Observation 8405db9a-57ca-421f-9e83-a2d34adf14a9 · outbound

This paper cites Space/aerial-assisted computing offloading for IoT applications: A learning-based approach,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Space/aerial-assisted computing offloading for IoT applications: A learning-based approach,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.248954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:29.213535Z digest=sha256:2b090b3124b683f384b35b80103fc7c9d77584df27d26f5cf3e3e69690b0060e

Observation be653337-de34-4765-96f3-aa68037dbe56 · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Toward environment-aware 6G communications via channel knowledge map,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:29.291368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:29.291368Z digest=sha256:c196a392ae37baea9fb47b82f1f44ddd4273a929ca685ae98ba733cb4ae100b5

Observation 9a1918ab-6e9e-499b-9ecf-8905b041cea8 · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication A tutorial on environment-aware communications via channel knowledge map for 6G,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.233506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:29.371839Z digest=sha256:c07c391a0dd1178d63177a376d2a8f370a16679134545ac3662db7d48b3ca83d

Observation bd538deb-02a9-48ff-b7ee-61df5821d024 · outbound

This paper cites Generative ai on spectrumnet: An open benchmark of multiband 3d radio maps,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Generative ai on spectrumnet: An open benchmark of multiband 3d radio maps,

Reference 16

Resolution
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raw_fallback, observed 2026-08-06T16:57:37.222936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:29.504165Z digest=sha256:d8dad7036425cc6aacc5094354342fdc3b63efffa1f440ac26bce5af919520e7

Observation 034b1798-1893-42b7-84d4-1c1027478577 · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication RadioUNet: Fast radio map estimation with convolutional neural networks,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:29.587451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:29.587451Z digest=sha256:10820ae56f862b7dbda52471d978e4b9ea2b3220d842be3551a8e4e1d693c429

Observation de55363b-d84d-4602-b4e4-f1b81fa0a8f7 · outbound

This paper cites Radiogat: A joint model-based and data-driven framework for multi-band radiomap reconstruction via graph attention networks,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Radiogat: A joint model-based and data-driven framework for multi-band radiomap reconstruction via graph attention networks,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.208077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:29.687666Z digest=sha256:7b835401857efe9567abf4b713dc856c24d69bb499f49c7b1f3ed626d9e573b9

Observation 39151f84-6c20-40f3-af14-1a9e81576b4b · outbound

This paper cites Ckmimagenet: A comprehensive dataset to enable channel knowledge map construction via computer vision,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Ckmimagenet: A comprehensive dataset to enable channel knowledge map construction via computer vision,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.198590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:29.788877Z digest=sha256:a3e7aa684ef92b7f9592757a0b0826f0970f3541162970734c1cc38f55375019

Observation c9730602-ee86-4156-823a-1b0abaa428c3 · outbound

This paper cites an unresolved cited work.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Unresolved cited work

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:29.889544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:29.889544Z digest=sha256:62548d59ff36f411d48277b31f52083fad4eec1d6cd044f43c1abe9fe73140cc

Observation c530b66e-42c1-4796-a7da-d784588b3a92 · outbound

This paper cites Ray techniques in electromagnetics,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Ray techniques in electromagnetics,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.181816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:29.970286Z digest=sha256:b86e314eed6a0045a8c382d5a229d4c884ab32d5a290a514d4d112e2c26bff2a

Observation 201fd7b6-7e1f-48e9-aa7d-eb42b13502bb · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication RME-GAN: A learning framework for radio map estimation based on conditional generative adversarial network,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.173203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.041207Z digest=sha256:a21d1a1772b06f975016487fa47b8bf5a7ff6940913a09e7a9f53b5ee0747f3d

Observation a1826e6f-673f-4b0d-a2d3-647b82817043 · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication A graph neural network based radio map construction method for urban environment,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.163796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.109386Z digest=sha256:ac8665a919827d35468ebf058b53607bdb0299ac1b9265938cc43f64168208ad

Observation 54b20551-76a9-4829-87f5-c33494d341d2 · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Radiodiff: An effective generative diffusion model for sampling-free dynamic radio map construction,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.154099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.192002Z digest=sha256:21e2a86ac91d8f605c1f1e6773290cfce1237b448540bb66227bd8278ce196fd

Observation c2958db8-b5cc-4d75-8a7e-381dce67de73 · outbound

This paper cites an unresolved cited work.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:57:37.145381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.291148Z digest=sha256:53a5a0af873d63e583c7f061b393b613402185416465881fd1f4c9e08a010c1b

Observation 9350347c-27d6-4da7-9f23-529562de59a4 · outbound

This paper cites Channel knowledge map construction based on a UA V-assisted channel measurement system,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Channel knowledge map construction based on a UA V-assisted channel measurement system,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.135890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.368207Z digest=sha256:b695b9136f1a42d5ed5a09cb41e6dbf045d46293a0f8a49aeb4c0e83428983d8

Observation 277f4ee6-dc6f-431e-a064-a9371b125ef3 · outbound

This paper cites Joint flying relay location and routing optimization for 6G UA V–IoT networks: A graph neural network-based approach,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Joint flying relay location and routing optimization for 6G UA V–IoT networks: A graph neural network-based approach,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.126352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.444192Z digest=sha256:94479520a6f1183031a95f0dcc38e0c928f71568d242f363c1f25908d3c20c91

Observation 7395b4bb-aeda-4e36-b5e5-d39b32433505 · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Locunet: Fast urban positioning using radio maps and deep learning,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.116291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.518893Z digest=sha256:8b89636e7bca89fdfb2e9ce083456daa2026229770bd3f1e3006bc39f607686b

Observation d8178231-8845-479b-88ff-17b85e0a4da2 · outbound

This paper cites Nearest neighbor pattern classification,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Nearest neighbor pattern classification,

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:30.591901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:30.591901Z digest=sha256:a03e45fe3d096f99b13206ff1fc4f4c3b4116de6d84ffbd2f201136373725edc

Observation 8d2e6d71-295a-4573-81d6-74b03129a529 · outbound

This paper cites Chiles and P.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Chiles and P

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.101892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.651321Z digest=sha256:1550710ab409a60545850b858bd72cfdef47dbaa3f47e66746ed58a6dffa1e05

Observation 12fea081-b576-4c02-be02-6952e7f6439f · outbound

This paper cites Informed spectrum usage in cognitive radio networks: Interference cartography,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Informed spectrum usage in cognitive radio networks: Interference cartography,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.093172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.791951Z digest=sha256:1f4e836a83fb903646ad2933039a89128124e44717c72f700390d879a2f04712

Observation b4f199aa-bb5e-406d-ac97-9155f3b7ee36 · outbound

This paper cites Local polynomial modelling and its applications,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Local polynomial modelling and its applications,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.083120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:30.911601Z digest=sha256:4264639ceb7c490ccd2589fd833ccd68130cffee86ff019e07aa72867a0ab878

Observation 37480b1e-190e-4ebd-ace3-70940402cd9a · outbound

This paper cites Regression assisted matrix completion for recon- structing a propagation field with application to source localization,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Regression assisted matrix completion for recon- structing a propagation field with application to source localization,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.073990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:31.045766Z digest=sha256:c235939d26a15114af08d75bb9d113ccf9370aed76d807395768a26d9be2028e

Observation dd4c2f2c-714c-43cd-b43e-8e94a71424d1 · outbound

This paper cites Cooperative spectrum sensing for cognitive radios using kriged kalman filtering,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Cooperative spectrum sensing for cognitive radios using kriged kalman filtering,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.064299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:31.233033Z digest=sha256:7ca1f1fdde9167b56bfc3e173f1cde6f0dc3b835ab1e640a53ab6356df4632b4

Observation 77d7387a-80b5-4450-bd85-dad30df1ba78 · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Channel gain map tracking via distributed kriging,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.054093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:31.381024Z digest=sha256:e2913b01944f3026ec7d2d24c3f7c6388f98a86022e5d65fb98259a1da9dd76d

Observation b4e99a55-fca8-4c4c-a79f-3247efb5214d · outbound

This paper cites Propagation map reconstruction via interpolation assisted matrix completion,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Propagation map reconstruction via interpolation assisted matrix completion,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.045413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:31.512567Z digest=sha256:5280b02768442cfe98bfb5d0ff5094d1b6ec086f697874140aefa1f0c337c739

Observation 65d0047c-e025-4f71-a15c-85b8a570c1f3 · outbound

This paper cites Spectrum cartography via coupled block-term tensor decomposition,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Spectrum cartography via coupled block-term tensor decomposition,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.035489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:31.678019Z digest=sha256:78066feae3a8bdd3faf39da59ab03934137386f8af222b526a9c925ca12baed0

Observation 827f8939-9d9d-47dd-9d98-dc2dc6ecd9ba · outbound

This paper cites Dual-kernel online re- construction of power maps,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Dual-kernel online re- construction of power maps,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.026727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:31.829151Z digest=sha256:dfb244f0bed321dcf321bdd079bdc5cae9d3a947d2a5b1f3840a858916a8ced0

Observation 1ec01e15-8340-4acb-96ad-e596d5f7867a · outbound

This paper cites Kriging-based interference power constraint: Integrated design of the radio environment map and transmission power,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Kriging-based interference power constraint: Integrated design of the radio environment map and transmission power,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.018112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:31.938335Z digest=sha256:52b6bbb8321f1bb61ae75eee83b7747d53cb0d2fa53a240fac17e1f6e67897cb

Observation 0d53b923-c789-4acd-ad4f-192d5db3db3c · outbound

This paper cites Map-based millimeter-wave channel models: An overview, data for b5g evaluation and machine learning,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Map-based millimeter-wave channel models: An overview, data for b5g evaluation and machine learning,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:32.063520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:32.063520Z digest=sha256:cd48d1f4671ca7168d8cc73aca5496ac3f61b88430b8a3182878468c785a6800

Observation 7dc12ad7-e11b-4f41-924c-22b170be2ab6 · outbound

This paper cites Map-based channel modeling and generation for u2v mmwave com- munication,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Map-based channel modeling and generation for u2v mmwave com- munication,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:37.005057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:32.215486Z digest=sha256:729976c25183a143e7828d755d62fe04c885b7c79e9511f6f1b2cffddc31022b

Observation 67b49896-1a28-4b5d-b530-4895f5859872 · outbound

This paper cites Spatial cover- age cross-tier correlation analysis for heterogeneous cellular networks,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Spatial cover- age cross-tier correlation analysis for heterogeneous cellular networks,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.997900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:32.363181Z digest=sha256:70b05218c3b3d07aeb7ab0304a1afe993256f7a67fb45746893672dfc36c56ac

Observation e615c81d-2a4e-4c55-9e1c-10422844720c · outbound

This paper cites Radiodiff-k 2: Helmholtz equation informed generative diffu- sion model for multi-path aware radio map construction,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Radiodiff-k 2: Helmholtz equation informed generative diffu- sion model for multi-path aware radio map construction,

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:32.790621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:32.790621Z digest=sha256:49e71650236ecd5a5b588f167653b0dbf0885e1cf84655f15080d7a853895373

Observation c5f88eed-916d-4711-a164-0b809d5f217f · outbound

This paper cites RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:32.916883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:32.916883Z digest=sha256:04049b35cc32beccd0354514852af87260b6534136a8fe2339edfc9a3d6eb668

Observation ed05ba41-d55e-42a7-a55b-2bd753bcb522 · outbound

This paper cites RadioNet: Robust deep-learning based radio fingerprinting,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication RadioNet: Robust deep-learning based radio fingerprinting,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.975818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:33.072581Z digest=sha256:518b4c5662c571ef1463cc1707c901bdb8a883e6c0fa9653c01b0a91feda3219

Observation e451e3ea-b30d-4c66-88a1-7d1ebfb6dd49 · outbound

This paper cites Efficient algorithms for air-to-ground channel reconstruction in uav-aided communications,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Efficient algorithms for air-to-ground channel reconstruction in uav-aided communications,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.968104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:33.215764Z digest=sha256:deb594359de6320239c4ffb66e2a3459c239244a6f17083a274fac495f23db09

Observation 1655901d-9bb6-4a8c-bf1f-569aafbe9391 · outbound

This paper cites Constructing radio maps for uav communications via dynamic resolution virtual obstacle maps,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Constructing radio maps for uav communications via dynamic resolution virtual obstacle maps,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.960424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:33.376504Z digest=sha256:c1e53045fda37814e8a9afac4cd02ee341e14885f286d905afdf7702436f7e92

Observation e37e3134-8209-498f-a4c6-c8a2eba21473 · outbound

This paper cites Geography-aware radio map reconstruction for uav-aided communications and localization,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Geography-aware radio map reconstruction for uav-aided communications and localization,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.953041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:33.511064Z digest=sha256:81964ed40a54874870d5c3e356fd80815f11bd49be092624f7143bfc921edecd

Observation 7d285c7a-eba8-45b6-962d-7f0a40f27b4f · outbound

This paper cites Nonparametric basis pursuit via sparse kernel-based learning: A unifying view with advances in blind methods,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Nonparametric basis pursuit via sparse kernel-based learning: A unifying view with advances in blind methods,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.944660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:33.639210Z digest=sha256:006373240326a868dff2929c67663e45d4131ba52fafaf878ea66e74ce1d3b83

Observation af73bbff-0691-4bbe-a79c-8d8b1ac91ba1 · outbound

This paper cites DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:33.768220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:33.768220Z digest=sha256:3f96c9368f2b6209dc6a6e6a5b29e55fd90db5e5bf8b2725f63df061fbb7386a

Observation 06abf3d1-4849-4650-83e1-f242ddbe0809 · outbound

This paper cites 5g channel model for bands up to100 ghz,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication 5g channel model for bands up to100 ghz,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.935768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:33.905450Z digest=sha256:e74350f6714c19e728c449614646608d136ea8a88032aea90e85f6928e51e7a9

Observation 775469bf-7077-408d-b31d-95f8fe3a7430 · outbound

This paper cites Deep completion autoencoders for radio map estimation,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Deep completion autoencoders for radio map estimation,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.990844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:34.024339Z digest=sha256:80f227eba3f54205c50f2a3a7515d75c4b50036c2dd6b8ef9cd00e4de97e9a3e

Observation f6771623-b5f5-4ca3-8240-e2201a0250f9 · outbound

This paper cites Accurate spectrum map construction for spectrum management through intelligent frequency-spatial reasoning,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Accurate spectrum map construction for spectrum management through intelligent frequency-spatial reasoning,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.927493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:34.105965Z digest=sha256:94ca933d1bff2b8bffca67db54b0c6a87a3b1f4b1da8fe5f1ce53677748e8351

Observation ddc137c8-a498-413e-9f87-62e6ff9e9dc0 · outbound

This paper cites Deep spectrum cartography: Com- pleting radio map tensors using learned neural models,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Deep spectrum cartography: Com- pleting radio map tensors using learned neural models,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.983221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:34.233161Z digest=sha256:eb5585bc3d887295535557dfba924bd7bfca9dab4abe19b484cddff835325d1f

Observation 3a04c251-63b4-40ea-bdc7-af7f2284cd9a · outbound

This paper cites Review on ray tracing channel simulation accuracy in sub-6 ghz outdoor deployment scenarios,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Review on ray tracing channel simulation accuracy in sub-6 ghz outdoor deployment scenarios,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.919056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:34.364297Z digest=sha256:ae18d741afebb8bae1797687efc5054d2f5539c2521070892d0be271fb7f176f

Observation 7c329aae-03af-455a-a837-c0e842e8c642 · outbound

This paper cites Field plotting and ray tracing in electron optics a review of numerical methods,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Field plotting and ray tracing in electron optics a review of numerical methods,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.911164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:34.502205Z digest=sha256:c9a03a24ce0d880d3f0a29bc6159a8c3d67c8370e38b924d966cae89378da859

Observation 20ac8827-ed30-4c01-811c-eae74765cfc5 · outbound

This paper cites Radio Map Estimation -- An Open Dataset with Directive Transmitter Antennas and Initial Experiments.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Radio Map Estimation -- An Open Dataset with Directive Transmitter Antennas and Initial Experiments

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:34.610715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:34.610715Z digest=sha256:f2bbd90baf260acf3684588b315561f7063cf4057e52b8938b32b4b4534fe59b

Observation 21e947e4-8ff2-4726-b39c-c7a586559ccb · outbound

This paper cites Generative adversarial networks: An overview,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Generative adversarial networks: An overview,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.902850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:34.722796Z digest=sha256:c79babff89c977d7c3f402b5ff9e4ad1b9c86e5df08e9e88137a99ea57b9ad85

Observation 73b7b32b-366c-4407-8752-7a178944551c · outbound

This paper cites Auto-encoding variational bayes,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Auto-encoding variational bayes,

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:34.812366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:34.812366Z digest=sha256:4f47dc7aaf03d77f384327fdaa455475488d20485480d423aa9f5d4381178a41

Observation e0524cec-81d3-406c-b8fa-4f7eb71497dc · outbound

This paper cites Confidence-Regulated Generative Diffusion Models for Reliable AI Agent Migration in Vehicular Metaverses.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Confidence-Regulated Generative Diffusion Models for Reliable AI Agent Migration in Vehicular Metaverses

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:34.945241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:57:34.945241Z digest=sha256:20d93eaa0c765e4fdf2c4ec67ed5ae47dc3a51bec3f80e6625a1612ed9ddbbeb

Observation e50accd2-b603-4528-9772-02df4b4cb98f · outbound

This paper cites Generative ai based secure wireless sensing for isac networks,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Generative ai based secure wireless sensing for isac networks,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.889442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:35.042000Z digest=sha256:c1bd5ae0b7295aaee77b05e3bfe3cef88dd8439d84cc40fa38d920677c050816

Observation a5c2bfdc-6f5d-4f45-8249-8864a13c3971 · outbound

This paper cites Generative ai meets wireless networking: An interactive paradigm for intent-driven communications,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Generative ai meets wireless networking: An interactive paradigm for intent-driven communications,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.881640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:35.146147Z digest=sha256:b19940fa8c0f115eaf945c2044de8e318e30710d7a8236ed19b62cc52a2b4504

Observation 0b5588ab-a997-48bd-aefb-79fe537307d6 · outbound

This paper cites Optimizing resource allocation for multi-modal semantic communication in mobile aigc networks: A diffusion-based game approach,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Optimizing resource allocation for multi-modal semantic communication in mobile aigc networks: A diffusion-based game approach,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.873229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:35.200691Z digest=sha256:62b7b4973855454da8ac2bfd91e2ca4f00189a7e1c26d8528bb83e7fa9e1f795

Observation 58b5efa1-0bc7-43dd-9853-13742fe35637 · outbound

This paper cites Maximum-Likelihood Estimation Based on Diffusion Model For Wireless Communications.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Maximum-Likelihood Estimation Based on Diffusion Model For Wireless Communications

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:35.258328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8a9cea81-f845-4cc5-809d-6a3ad28d5728 · outbound

This paper cites Diffusion models in vision: A survey,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Diffusion models in vision: A survey,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.864092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b0c00486-a345-4492-b496-1426021aa9c2 · outbound

This paper cites Denoising diffusion probabilistic models,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Denoising diffusion probabilistic models,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.855385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:57:35.387473Z digest=sha256:d3f493aba5645e7951bf12810256237e5736787ddac69b60d02232aad673926a

Observation 8c649538-e0da-45e9-8bc1-8d6ac5f9d45c · outbound

This paper cites Denoising diffusion implicit models,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Denoising diffusion implicit models,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.586257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 54ab90ff-17f8-4ed5-a0f1-39c857576b90 · outbound

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

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication Dominant path prediction model for urban scenarios,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:36.214713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2083ccb3-9c37-4bea-90dc-d4c5612bb052 · outbound

This paper cites 3d u-net: Learning dense volumetric segmentation from sparse annotation,.

RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication 3d u-net: Learning dense volumetric segmentation from sparse annotation,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:57:35.803769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Pith citing papers

Observation 75207193-5e9c-4450-b524-58f254c6dd38 · inbound

WiSER: A Wireless Scene Encoder for Geometry-Grounded Multi-View Wireless Prediction cites this paper.

WiSER: A Wireless Scene Encoder for Geometry-Grounded Multi-View Wireless Prediction RadioDiff-3D: A 3D$\times$3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-02T10:16:52.303130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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