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Paper Citation Record · LEDGER

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization

As of 10 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2607.08045.

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

pith.paper-citation-record.v1
2607.08045 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T01:14:26.651640Z

measured 46 of 46 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

  • verified exact7
  • verified fuzzy38
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f4392a32-f428-4b31-bac2-33834b1efcd4 · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization 6G omni-scenario on-demand services provisioning: vision, technology and prospect(in chinese),

Reference 1

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raw_fallback, observed 2026-07-10T01:16:41.454768Z

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 9460a57c-07ac-47ba-8917-88b19723efe2 · outbound

This paper cites 5g channel model for bands up to 100 ghz,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization 5g channel model for bands up to 100 ghz,

Reference 2

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raw_fallback, observed 2026-07-10T01:16:41.453618Z

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

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Observation 35e7ae34-05b2-4457-adc9-acd6bbbbbd5e · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization RadioNet: Robust deep-learning based radio fingerprinting,

Reference 3

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raw_fallback, observed 2026-07-10T01:16:41.445299Z

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

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Observation a366ead9-520d-4251-968d-5c520c6c3877 · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Generative ai on spectrumnet: An open benchmark of multiband 3d radio maps,

Reference 4

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raw_fallback, observed 2026-07-10T01:16:41.455465Z

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=2026-07-10T01:14:26.651640Z digest=sha256:fa666da08377b6a590435dcac67fbe6fc09ae179db8939a069ebb7007795348e

Observation bac01a66-a150-4ee4-b9ff-f8bacc53dc26 · outbound

This paper cites Generative ai for deep reinforcement learning: Framework, analysis, and use cases,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Generative ai for deep reinforcement learning: Framework, analysis, and use cases,

Reference 5

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raw_fallback, observed 2026-07-10T01:16:41.457450Z

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=2026-07-10T01:14:26.651640Z digest=sha256:694567ffe80a8da590b0288a4011ba5e6a4cb16ffeb846848bf6e31c75b9611e

Observation 7a70138a-078f-4723-b526-949cc49bfce4 · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization RadioUNet: Fast radio map estimation with convolutional neural networks,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.441903Z

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=2026-07-10T01:14:26.651640Z digest=sha256:302854a98647dbbbf9e13bb32f8bc482b558104a7a57f62bf34d51a01ed59562

Observation f178bd0c-53c3-4280-b0fa-040fd3ff701c · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Radiodiff: An effective generative diffusion model for sampling-free dynamic radio map construction,

Reference 7

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raw_fallback, observed 2026-07-10T01:16:41.456648Z

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=2026-07-10T01:14:26.651640Z digest=sha256:2f400489c19b4f9a9df08d09b6807ae2c8ab90974027e5fbda520cb0d8d0ff16

Observation d2430f45-cb05-4552-9c0a-4518a903e7f1 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization U-net: Convolutional networks for biomedical image segmentation

Reference 8

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raw_fallback, observed 2026-07-10T01:16:41.463922Z

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=2026-07-10T01:14:26.651640Z digest=sha256:37e5154024fd722c254debc2f61736517a8bd7f46bef57421bd4384ac655d702

Observation d87f82a1-177f-4963-9201-4fafbad7520b · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization RME-GAN: A learning framework for radio map estimation based on conditional generative adversarial network,

Reference 9

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raw_fallback, observed 2026-07-10T01:16:41.420238Z

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=2026-07-10T01:14:26.651640Z digest=sha256:c74c64dd45c92e6931bf9164b9d33a1928919d5f72a303faacb1ac26ac8969c3

Observation 66be71ee-4097-4b8c-9e68-c1060dbb7f54 · outbound

This paper cites Generative adversarial networks: An overview,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Generative adversarial networks: An overview,

Reference 10

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raw_fallback, observed 2026-07-10T01:16:41.417729Z

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

source=pdf_text observed=2026-07-10T01:14:26.651640Z digest=sha256:52584fda979aa75222a5311e23045037faf1f8133c4f1cfba3f9ed3874889ff9

Observation 26a07804-8a31-4f17-9546-20e57d2a9d9b · outbound

This paper cites Radiodiff-k2: Helmholtz equation informed generative diffusion model for multi-path aware radio map construction.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Radiodiff-k2: Helmholtz equation informed generative diffusion model for multi-path aware radio map construction

Reference 11

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

source=pdf_text observed=2026-07-10T01:14:26.651640Z digest=sha256:473e692a4cbbe6cf9bcc00e2dc81b6a66df1af72191f10a6ad27787b5becbf86

Observation 787885de-bdac-419b-a09d-b1ae1bf1cb61 · outbound

This paper cites The perception-distortion tradeoff.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization The perception-distortion tradeoff

Reference 12

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raw_fallback, observed 2026-07-10T01:16:41.424578Z

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=2026-07-10T01:14:26.651640Z digest=sha256:860648c284e1500253e14da8855bf39927b432366944d503752c14691d5e38c7

Observation 61d94211-a9e7-4509-b0b8-0cf4dcbe115d · outbound

This paper cites Flow matching for generative modeling.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Flow matching for generative modeling

Reference 13

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raw_fallback, observed 2026-07-10T01:16:41.478497Z

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=2026-07-10T01:14:26.651640Z digest=sha256:bf1d4c57627c277b6bb3e4ca7c77ec27b478564e61ee66cabdf4478add92d9c8

Observation bbe20095-78a0-493a-bdee-8ef4d8b8ec31 · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Flow straight and fast: Learning to generate and transfer data with rectified flow

Reference 14

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verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.413487Z

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=2026-07-10T01:14:26.651640Z digest=sha256:6f6b42e7723308e5de1b25bb45f4f460e6205cca396357ef67ff47148a384ac3

Observation 7ca0dde0-bca6-4018-b209-2fe7d8ea9554 · outbound

This paper cites Scalable diffusion models with transformers,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Scalable diffusion models with transformers,

Reference 15

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raw_fallback, observed 2026-07-10T01:16:41.415524Z

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=2026-07-10T01:14:26.651640Z digest=sha256:0353e03b33e683924ef4c9ea2ba60ee572f2c42e50ea647aa70d76d31cec4d82

Observation bc896a90-a8b5-44c1-8517-23187f3fd59e · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Locunet: Fast urban positioning using radio maps and deep learning,

Reference 16

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raw_fallback, observed 2026-07-10T01:16:41.405171Z

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

source=pdf_text observed=2026-07-10T01:14:26.651640Z digest=sha256:b96fbdcd1a40e03c6d409416c9f4057c717baccad9932df74b15d501dab77338

Observation de4d3f0e-26e9-471f-800f-2cfaae9ffee8 · outbound

This paper cites Indoor radio map construction and localization with deep gaussian processes,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Indoor radio map construction and localization with deep gaussian processes,

Reference 17

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raw_fallback, observed 2026-07-10T01:16:41.407039Z

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=2026-07-10T01:14:26.651640Z digest=sha256:41fa8b9e4b201e85f21f29e56a7c64b1e763d157860749df760e69c6650f7e57

Observation bea35f3b-2812-40a3-9824-4a62a1328b0f · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Toward environment-aware 6G communications via channel knowledge map

Reference 18

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raw_fallback, observed 2026-07-10T01:16:41.420467Z

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=2026-07-10T01:14:26.651640Z digest=sha256:b33daf62b5400ea0688e72e8e93d8ab806a64d9cc3ed4da993a896cb4abbd0cd

Observation 3f9b8611-9f77-4ec3-ac13-a0ee7df65c9a · outbound

This paper cites A Tutorial on Learning-Based Radio Map Construction: Data, Paradigms, and Physics-Awareness.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization A Tutorial on Learning-Based Radio Map Construction: Data, Paradigms, and Physics-Awareness

Reference 19

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local_arxiv, observed 2026-07-10T01:16:41.157291Z

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=2026-07-10T01:14:26.651640Z digest=sha256:5ea15a480fe3e7f6a8d2eca193cf4269240fb4b6b79b09dd5ab10af9d80bba97

Observation f5f48e6d-c755-49a9-a183-745389d56862 · outbound

This paper cites Radiodiff-inverse: Diffusion enhanced bayesian inverse estimation for isac radio map construction,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Radiodiff-inverse: Diffusion enhanced bayesian inverse estimation for isac radio map construction,

Reference 20

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raw_fallback, observed 2026-07-10T01:16:41.465993Z

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=2026-07-10T01:14:26.651640Z digest=sha256:5219610f95d219e1d1b810e972578ca976fb95f6c33a2c50af304a09c5bfe715

Observation 4a479dc9-4fe6-40be-aa9c-84e30ee6b2fd · outbound

This paper cites iRadioDiff: Physics-informed diffusion model for indoor radio map construction and localization,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization iRadioDiff: Physics-informed diffusion model for indoor radio map construction and localization,

Reference 21

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arxiv_id, observed 2026-07-10T01:16:41.175093Z

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=2026-07-10T01:14:26.651640Z digest=sha256:c822a044729ff8cc4d038991bfb6dbe5d2b2d995ac1114922188aa7337445e1a

Observation 426fa800-0add-4e7a-8ad5-bbcf14ff8665 · outbound

This paper cites RadioDiff-FS: Physics-informed manifold alignment in few-shot diffusion models for high-fidelity radio map construction,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization RadioDiff-FS: Physics-informed manifold alignment in few-shot diffusion models for high-fidelity radio map construction,

Reference 22

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arxiv_id, observed 2026-07-10T01:16:41.168145Z

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=2026-07-10T01:14:26.651640Z digest=sha256:6775e51e1e6258c30c2950ffcfb9b1b30d60611e38ede3671cdcf5019b44e0c9

Observation e13e2578-09f8-47a3-adb2-a925e7aaf30a · outbound

This paper cites RadioDiff-flux: Efficient radio map construction via generative denoise diffusion model trajectory midpoint reuse,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization RadioDiff-flux: Efficient radio map construction via generative denoise diffusion model trajectory midpoint reuse,

Reference 23

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raw_fallback, observed 2026-07-10T01:16:41.477999Z

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=2026-07-10T01:14:26.651640Z digest=sha256:3662cf10e5b9d154c4b3d5c7026336b848a75993ad213ef138388671a3dd462b

Observation 431841a4-7685-43f1-ac09-7baa13e7998d · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Radiogat: A joint model-based and data-driven framework for multi-band radiomap reconstruction via graph attention networks,

Reference 24

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raw_fallback, observed 2026-07-10T01:16:41.486415Z

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=2026-07-10T01:14:26.651640Z digest=sha256:aba15f0a52601bc156c02445443d7e9dff6a4cd8df40cd2778097a62a09f445d

Observation 811ce76c-eb56-4e77-92bc-13fae4d505e7 · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Radio Map Estimation -- An Open Dataset with Directive Transmitter Antennas and Initial Experiments

Reference 25

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metadata mismatch
local_arxiv, observed 2026-07-10T01:16:41.162844Z

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=2026-07-10T01:14:26.651640Z digest=sha256:d8e5847edf08dad802e31e628f0f9aca7e378c08e010702a187c58989a43daf5

Observation 020dcd95-394b-4696-bcd9-c0c21a4d91b2 · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Ckmimagenet: A comprehensive dataset to enable channel knowledge map construction via computer vision,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.488375Z

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=2026-07-10T01:14:26.651640Z digest=sha256:5e8213e9800b8fb5932fa47a85c06386ab3783c445976a4a802d09e6556ddcd5

Observation 1f474436-43d3-4b82-a1bd-cbbc487fa1f0 · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization RadioDiff-3D: A 3D×3D radio map dataset and generative diffusion based benchmark for 6G environment-aware communication

Reference 27

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raw_fallback, observed 2026-07-10T01:16:41.472205Z

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=2026-07-10T01:14:26.651640Z digest=sha256:c40c4ed00edeaa8b9a79a4ea7569fd0f03c1a0372a8371acef40aeaa2b814288

Observation 2ff3b298-714f-40d7-ba7f-565e8b57c37a · outbound

This paper cites Denoising diffusion probabilistic models,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Denoising diffusion probabilistic models,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.473944Z

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=2026-07-10T01:14:26.651640Z digest=sha256:aa733d0a48a797f974554baf3173c3a5635c5e2c0d053398305dd47ce71f4d71

Observation cdf4dade-bf11-400a-bea5-ef2bc1d31725 · outbound

This paper cites Denoising diffusion implicit models,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Denoising diffusion implicit models,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.475952Z

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=2026-07-10T01:14:26.651640Z digest=sha256:42c93818d8d83c29ff8f0fe29a5fcd9ad084dcdb235d834a6f77dbb738461c81

Observation faa3ac0b-d070-4208-b977-4f108c38910d · outbound

This paper cites Score-based generative modeling through stochastic differ- ential equations.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Score-based generative modeling through stochastic differ- ential equations

Reference 30

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raw_fallback, observed 2026-07-10T01:16:41.479976Z

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=2026-07-10T01:14:26.651640Z digest=sha256:47e91a7615cf78153b390dacd07674357f0c96edd06fd914e0193eeaf787b86f

Observation d3199f05-cf68-41a0-a5ac-0206e3596723 · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization High-resolution image synthesis with latent diffusion models,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.449430Z

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=2026-07-10T01:14:26.651640Z digest=sha256:c986ab48b9d7ba2d60fadeaa9ed76af80086619f8f5f2a78aa4ed0a207bf2be2

Observation db8bf888-eebe-42a3-8a2d-298ebdd6ef3c · outbound

This paper cites Glide: Towards photorealistic image gener- ation and editing with text-guided diffusion models,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Glide: Towards photorealistic image gener- ation and editing with text-guided diffusion models,

Reference 32

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verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.468273Z

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=2026-07-10T01:14:26.651640Z digest=sha256:1971b44e596e8e663abe62af495e42da557f8d5525b3e8c2d0e902809f051e90

Observation 537dbbca-6d61-483f-a81b-0a01e63c796a · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image Attenuation

Reference 33

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verified exact
local_arxiv, observed 2026-07-10T01:16:41.171759Z

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 4b34a493-95a3-46d5-b650-1b1044a68ad5 · outbound

This paper cites Attention is all you need,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Attention is all you need,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.431057Z

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=2026-07-10T01:14:26.651640Z digest=sha256:81e9d40fb4902b337f63d39f4f3486c48fad2c49a36dcc486945095588a22ce6

Observation 2eeabd35-bb26-465a-96fe-78ff01de5ddc · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Diffusion models in vision: A survey,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.428197Z

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=2026-07-10T01:14:26.651640Z digest=sha256:e27a34b9045a0f36701b4570e912d7ab2e2add4f28df10c841b1eac730805bbb

Observation e12fc75b-1728-4a82-8fcc-77bfbe8c8093 · outbound

This paper cites Exploiting radio fingerprints for simultaneous localization and mapping,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Exploiting radio fingerprints for simultaneous localization and mapping,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.464109Z

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=2026-07-10T01:14:26.651640Z digest=sha256:91d755cdfca701a3241668e5419bbfa6824f479cd7d1aa1f76fe6b90c5b22a1e

Observation 7d44bc57-7f1f-48e0-81bd-f599c8a9b2b9 · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Confidence-Regulated Generative Diffusion Models for Reliable AI Agent Migration in Vehicular Metaverses

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-07-10T01:16:41.177263Z

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=2026-07-10T01:14:26.651640Z digest=sha256:da271e5f6a99cb75a4f33a8b4f458172dde9c32c1270c78b53b0b7e47e2a81cf

Observation cf9393fb-5f1c-4931-b6c3-7268b15080ca · outbound

This paper cites Electromagnetic scattering laws in weyl systems,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Electromagnetic scattering laws in weyl systems,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.481860Z

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=2026-07-10T01:14:26.651640Z digest=sha256:9988064ac226d0e85dfc3b6a02b6d3d5ec95a5e1aa877aa92fa5a53f78ce3984

Observation 913d1f66-ece3-4e9f-b2c8-cc44490456be · outbound

This paper cites Ray techniques in electromagnetics.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Ray techniques in electromagnetics

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.490236Z

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=2026-07-10T01:14:26.651640Z digest=sha256:756570183eb2ef294a6438fa5853b4970835319604c89d039b5c5814d5772212

Observation 16c46060-c3fe-4c0f-b7aa-cc41b733a3a6 · outbound

This paper cites Map2APS: A Physically Grounded Benchmark for Direct Angle Power Spectrum Prediction from Urban Geometry.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Map2APS: A Physically Grounded Benchmark for Direct Angle Power Spectrum Prediction from Urban Geometry

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-07-10T01:16:41.171784Z

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=2026-07-10T01:14:26.651640Z digest=sha256:b952fa2af28149700ccbe97ea25cc5332a2b320581b23c6625a3d2fee805206c

Observation e202b8a8-1eb8-4bdb-8bf9-9f602b8ba70f · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-07-10T01:16:41.174499Z

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=2026-07-10T01:14:26.651640Z digest=sha256:c459768e91590cee61099e5e0cbe3b1132d9d4b7bd645efd8718ba0af6d107ac

Observation 11f4fc36-8c6b-4ed8-b465-72e5159da4de · outbound

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

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Dominant path prediction model for urban scenarios,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.488159Z

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=2026-07-10T01:14:26.651640Z digest=sha256:816e6ae06dec229d6966ac0a834bb76be6d4702a217a50fc38d54bd3740dbf71

Observation 8a422d39-440f-4a51-968e-1426e2eb8a4e · outbound

This paper cites Classifier-free diffusion guidance.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Classifier-free diffusion guidance

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.466139Z

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=2026-07-10T01:14:26.651640Z digest=sha256:8a9f2295bd95182a1c4012562fcb71516d08a7e321052c6975d354f7a3eb8bca

Observation 58da5ee8-7586-46a2-8d01-6b996a044159 · outbound

This paper cites Computational optimal transport: With appli- cations to data science,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Computational optimal transport: With appli- cations to data science,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.492531Z

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=2026-07-10T01:14:26.651640Z digest=sha256:cf1ad86af58058ae2e7978a862238e51bfdf5d0001e4c507c6f3a52c5d9d4fd2

Observation e0d62c03-aa67-4171-8da9-6768c31d736c · outbound

This paper cites Digital mobile radio towards future gen- eration systems—COST action 231 final report,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Digital mobile radio towards future gen- eration systems—COST action 231 final report,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.483712Z

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=2026-07-10T01:14:26.651640Z digest=sha256:4230a96f1d610cd9a4e8fd7b189817b56ca76ce0634bd855dcc9f92182482448

Observation f29a6ddc-e70a-430f-a708-93d8d9e75719 · outbound

This paper cites Image quality assessment: from error visibility to structural similarity,.

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization Image quality assessment: from error visibility to structural similarity,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T01:16:41.485814Z

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=2026-07-10T01:14:26.651640Z digest=sha256:70a9ddbf11d13e0b7b488a0b35c4db72a5c64acf0ef6822ff515f49b0f8c9fde

Pith citing papers

No inbound Pith citation observations are available.