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Paper Citation Record · LEDGER

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation

As of 9 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2607.11429.

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

pith.paper-citation-record.v1
2607.11429 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T05:39:47.587160Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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.

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Reference resolution

19 of 19 outbound references displayed

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External citation measurements

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Outbound references

Observation b951d556-f691-474a-923b-41114ea990e8 · outbound

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

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Study on channel model for frequencies from 0.5 to 100 GHz,

Reference 1

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Observation 300f63e3-0e47-4ac4-9d8f-1f97d2039b8a · outbound

This paper cites Sionna: An Open-Source Library for Next-Generation Physical Layer Research.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Sionna: An Open-Source Library for Next-Generation Physical Layer Research

Reference 2

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Observation 9c03f607-4127-4b46-9d8e-b52a7426d488 · outbound

This paper cites Evaluation of the spatial consistency feature in the 3GPP geometry-based stochastic channel model,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Evaluation of the spatial consistency feature in the 3GPP geometry-based stochastic channel model,

Reference 3

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Observation 649ac0b5-27da-40ed-b803-df8953a68af1 · outbound

This paper cites Flexible 3GPP MIMO channel modeling and calibration with spatial consistency,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Flexible 3GPP MIMO channel modeling and calibration with spatial consistency,

Reference 4

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Observation 43fa2fd3-3ef3-45bd-b544-e12a1f768a80 · outbound

This paper cites Deep sets,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Deep sets,

Reference 5

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Observation f1b0febd-d491-4c9a-b666-c48e92de41dd · outbound

This paper cites Set transformer: A framework for attention-based permutation-invariant neural networks,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Set transformer: A framework for attention-based permutation-invariant neural networks,

Reference 6

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Observation 956f3609-20f9-4200-9b5e-54ddeff736db · outbound

This paper cites Generative- adversarial-network-based wireless channel modeling: Challenges and opportunities,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Generative- adversarial-network-based wireless channel modeling: Challenges and opportunities,

Reference 7

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Observation 3a274db7-92dc-4248-af9d-7352e2ac2b2b · outbound

This paper cites Generative adversarial estimation of channel covariance in vehicular millimeter wave systems,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Generative adversarial estimation of channel covariance in vehicular millimeter wave systems,

Reference 8

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Observation 8074e2e7-4427-4a05-8283-ed27b350921e · outbound

This paper cites MIMO-GAN: Generative MIMO channel modeling,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation MIMO-GAN: Generative MIMO channel modeling,

Reference 9

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Observation 36d43286-d563-4981-9f07-ed717487add2 · outbound

This paper cites GAN-based massive MIMO channel model trained on measured data,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation GAN-based massive MIMO channel model trained on measured data,

Reference 10

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Observation a5296304-7ac0-4740-85b5-02e823b1e129 · outbound

This paper cites Diffusion models for wireless communications,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Diffusion models for wireless communications,

Reference 11

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Observation aaf5b87d-ebdd-428a-b504-a4384504bcbf · outbound

This paper cites Generative diffusion models for wireless networks: Fundamental, architecture, and state-of- the-art,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Generative diffusion models for wireless networks: Fundamental, architecture, and state-of- the-art,

Reference 12

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Observation 16b3f613-b977-4394-b2b0-d19bc8796bf4 · outbound

This paper cites Digital twin of channel: Diffusion model for sensing-assisted statistical channel state information generation,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Digital twin of channel: Diffusion model for sensing-assisted statistical channel state information generation,

Reference 13

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Observation 87e5bade-dcc2-40d6-9d92-96512ce3b3dd · outbound

This paper cites Generating high dimen- sional user-specific wireless channels using diffusion models,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Generating high dimen- sional user-specific wireless channels using diffusion models,

Reference 14

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Observation 8c4ba82b-0c8a-4679-9fb4-9ef7c9c7f90d · outbound

This paper cites Random features for large-scale kernel machines,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Random features for large-scale kernel machines,

Reference 15

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Observation 31f164bc-5f25-4c8f-82fe-f3a93fbe1046 · outbound

This paper cites Wasserstein generative adver- sarial networks,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Wasserstein generative adver- sarial networks,

Reference 16

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Observation c214e5d7-46d2-4b86-a14d-b402095d9b49 · outbound

This paper cites Spectral normal- ization for generative adversarial networks,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Spectral normal- ization for generative adversarial networks,

Reference 17

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Observation 43f8d9f3-a6b0-4037-b536-e8b7c16186b5 · outbound

This paper cites Pareto GAN: Extending the representational power of GANs to heavy-tailed distributions,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Pareto GAN: Extending the representational power of GANs to heavy-tailed distributions,

Reference 18

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Observation a07d3ad5-e1a8-4ff8-9762-6b26703dc61c · outbound

This paper cites Top-ktraining of GANs: Improving GAN performance by throwing away bad samples,.

Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation Top-ktraining of GANs: Improving GAN performance by throwing away bad samples,

Reference 19

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Pith citing papers

No inbound Pith citation observations are available.