Paper Citation Record · LEDGER

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models

As of 19 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2512.20108.

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

pith.paper-citation-record.v1
2512.20108 v2

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measured 42 of 42 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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42 of 42 outbound references displayed

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Outbound references

Observation beb04690-b462-4541-911a-295bb060f5d9 · outbound

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

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Informed spectrum usage in cognitive radio networks: Interference cartography,

Reference 1

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Observation 410fd73d-c34d-40e7-8a98-57868fa9f755 · outbound

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

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Deep spectrum cartography: Complet- ing radio map tensors using learned neural models,

Reference 2

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Observation bdd98b64-c98b-4e47-94bb-c650fc087166 · outbound

This paper cites Spec- trum cartography techniques, challenges, opportunities, and applications: A survey,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Spec- trum cartography techniques, challenges, opportunities, and applications: A survey,

Reference 3

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This paper cites A low-complexity return-link beam-hopping scheduling for ngso mega-constellations with dynamic topology and uneven traffic,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models A low-complexity return-link beam-hopping scheduling for ngso mega-constellations with dynamic topology and uneven traffic,

Reference 4

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Observation 8433fad4-306a-4eb4-a27a-69fdbec92ab6 · outbound

This paper cites Satellite-terrestrial coordinated multi-satellite beam hopping scheduling based on multi- agent deep reinforcement learning,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Satellite-terrestrial coordinated multi-satellite beam hopping scheduling based on multi- agent deep reinforcement learning,

Reference 5

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Observation a5ae99e7-ceda-4977-83a5-9fe8289ce50d · outbound

This paper cites Spectrum Map and Its Application in Resource Management in Cognitive Radio Networks,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Spectrum Map and Its Application in Resource Management in Cognitive Radio Networks,

Reference 6

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Observation 6bd3aafa-d16b-46af-a5e0-7534c7696699 · outbound

This paper cites Reliability of a radio environment map: Case of spatial interpolation techniques,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Reliability of a radio environment map: Case of spatial interpolation techniques,

Reference 7

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Observation d5c7172f-9869-412a-9d4b-88cbc20767b7 · outbound

This paper cites Group-lasso on splines for spectrum cartography,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Group-lasso on splines for spectrum cartography,

Reference 8

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Observation 1ac359c9-5a99-42d7-a3fb-d01f6edfb812 · outbound

This paper cites Non-parametric spectrum cartogra- phy using adaptive radial basis functions,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Non-parametric spectrum cartogra- phy using adaptive radial basis functions,

Reference 9

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This paper cites Wire- less sensor network for spectrum cartography based on kriging interpola- tion,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Wire- less sensor network for spectrum cartography based on kriging interpola- tion,

Reference 10

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Observation 950464fb-0d83-47ec-b56b-7d23386e799b · outbound

This paper cites Compressive multispectral spectrum sensing for spectrum cartography,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Compressive multispectral spectrum sensing for spectrum cartography,

Reference 11

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Observation 96a452bf-e19f-4575-9ede-721e03bcc03f · outbound

This paper cites Improved performance of spectrum cartography based on compressive sensing in cognitive radio networks,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Improved performance of spectrum cartography based on compressive sensing in cognitive radio networks,

Reference 12

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Observation e67308a7-8ccd-4480-b58a-4f56db256d6f · outbound

This paper cites Distributed spectrum sensing for cognitive radio networks by exploiting sparsity,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Distributed spectrum sensing for cognitive radio networks by exploiting sparsity,

Reference 13

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Observation ba386395-e9cf-4d35-b9da-00f42a787a8b · outbound

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

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Spectrum cartog- raphy via coupled block-term tensor decomposition,

Reference 14

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Observation aa033fce-deea-40e3-9729-ded548bd8040 · outbound

This paper cites Spectrum cartography using quantized observations,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Spectrum cartography using quantized observations,

Reference 15

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Observation b6952b7d-7db4-490f-8ce5-fd4e32a64419 · outbound

This paper cites Spatiotemporal correlation analysis and visualization of electromagnetic intensity based on multi- site and multi-time attention mechanism,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Spatiotemporal correlation analysis and visualization of electromagnetic intensity based on multi- site and multi-time attention mechanism,

Reference 16

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Observation dfa90179-8287-4e70-9028-9384b0df9d70 · outbound

This paper cites Sc- gan: A spectrum cartography with satellite internet based on pix2pix generative adversarial network,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Sc- gan: A spectrum cartography with satellite internet based on pix2pix generative adversarial network,

Reference 17

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Observation bf0b21ca-8e11-4b51-a235-7df7ba583d55 · outbound

This paper cites Generative modeling by estimating gradients of the data distribution,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Generative modeling by estimating gradients of the data distribution,

Reference 18

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Observation d4ce06cd-6574-41e0-aa09-3ea8e74ec6a0 · outbound

This paper cites Denoising diffusion probabilistic models,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Denoising diffusion probabilistic models,

Reference 19

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Observation 092a5198-8ba3-455d-b61c-cffecb4102b9 · outbound

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Improved denoising diffusion probabilis- tic models,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Denoising Diffusion Implicit Models

Reference 21

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This paper cites Diffusion posterior sampling for linear inverse problem solving: A filtering perspective,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Diffusion posterior sampling for linear inverse problem solving: A filtering perspective,

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Observation 489f652c-dfd7-4470-a98b-e90d275a06be · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 23

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Observation c42a6287-6c50-49f0-a5a8-4e75508212f0 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 24

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Observation 7d8aed49-e4df-4e73-8c43-7f844e79f44d · outbound

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Flow Matching for Generative Modeling

Reference 25

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This paper cites Improving diffusion inverse problem solving with decoupled noise an- nealing,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Improving diffusion inverse problem solving with decoupled noise an- nealing,

Reference 26

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Observation 746030a2-d482-4724-a469-9c8019225b7d · outbound

This paper cites Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model

Reference 27

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Observation 1a8f23b4-79e2-4660-a091-13a696f3afa5 · outbound

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Denoising diffusion restoration models,

Reference 28

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Diffusion posterior sampling for general noisy inverse problems,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Diffusion model based posterior sampling for noisy linear inverse problems,

Reference 30

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Pseudoinverse-guided diffusion models for inverse problems,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Deep bayesian active learning with image data,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Uncertainty-guided perturbation for image super-resolution diffusion model,

Reference 33

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Radiodiff: An effective generative diffusion model for sampling-free dynamic radio map construction,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Quantized compressed sensing with score- based generative models,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Compressed sensing with quan- tized measurements,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Qcs-sgm+: Improved quantized com- pressed sensing with score-based generative models,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Bayes-optimal joint channel-and-data estimation for massive mimo with low-precision adcs,

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This paper cites Reliability of a radio environment map: Case of spatial interpolation techniques,.

Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Reliability of a radio environment map: Case of spatial interpolation techniques,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Domain-factored untrained deep prior for spectrum cartography,

Reference 40

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models Image quality assess- ment: from error visibility to structural similarity,

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Generative Spectrum Cartography: Unified Reconstruction and Active Sensing via Diffusion Models The unreasonable effectiveness of deep features as a perceptual metric,

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Pith citing papers

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