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Paper Citation Record · LEDGER

A look at adversarial attacks on radio waveforms from discrete latent space

As of 10 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2506.09896.

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

pith.paper-citation-record.v1
2506.09896 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:42:06.329918Z

measured 22 of 22 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

22 of 22 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 84a84c79-7f59-4137-837c-123feaf9f2ed · outbound

This paper cites ReFormer: Generating Radio Fakes from the Learned Channel Prior,.

A look at adversarial attacks on radio waveforms from discrete latent space ReFormer: Generating Radio Fakes from the Learned Channel Prior,

Reference 1

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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 dc43c2c6-a2d1-4509-a212-0e1d1d31bf46 · outbound

This paper cites Adversarial examples in rf deep learning: Detection and physical robustness,.

A look at adversarial attacks on radio waveforms from discrete latent space Adversarial examples in rf deep learning: Detection and physical robustness,

Reference 2

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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 b4f9da94-0940-43e0-b574-1b75a42212ee · outbound

This paper cites Mitigation of adversarial examples in rf deep classifiers utilizing autoencoder pre-training,.

A look at adversarial attacks on radio waveforms from discrete latent space Mitigation of adversarial examples in rf deep classifiers utilizing autoencoder pre-training,

Reference 3

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Source-reported events for the cited work

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Observation 9f2a935c-7066-44c6-8a8e-3050f1660d89 · outbound

This paper cites Adversarial attacks on deep-learning based radio signal classification,.

A look at adversarial attacks on radio waveforms from discrete latent space Adversarial attacks on deep-learning based radio signal classification,

Reference 4

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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 96cc7e63-6760-457d-9a62-ef059a43838b · outbound

This paper cites Channel-aware adversarial attacks against deep learning-based wireless signal classifiers,.

A look at adversarial attacks on radio waveforms from discrete latent space Channel-aware adversarial attacks against deep learning-based wireless signal classifiers,

Reference 5

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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 eb7070c3-8654-4e73-b88a-b141f00197a4 · outbound

This paper cites Adversarial examples detection of radio signals based on multifeature fusion,.

A look at adversarial attacks on radio waveforms from discrete latent space Adversarial examples detection of radio signals based on multifeature fusion,

Reference 6

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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 5bfb0efa-ba96-473a-81bb-020f97fe16fb · outbound

This paper cites Adversarial samples detection based on feature attribution and contrast in modulation recognition,.

A look at adversarial attacks on radio waveforms from discrete latent space Adversarial samples detection based on feature attribution and contrast in modulation recognition,

Reference 7

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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 a142c9d6-f2aa-4095-a3e5-a3d9bb789bc7 · outbound

This paper cites MIMO Channel Estimation Using Score- Based Generative Models,.

A look at adversarial attacks on radio waveforms from discrete latent space MIMO Channel Estimation Using Score- Based Generative Models,

Reference 8

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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 6fad02f3-7df4-4669-b274-f89e48b45be3 · outbound

This paper cites Score-Based Generative Models for Robust Channel Estimation,.

A look at adversarial attacks on radio waveforms from discrete latent space Score-Based Generative Models for Robust Channel Estimation,

Reference 9

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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 a28e4a58-667c-4b5e-b16b-3fe28c9e3b54 · outbound

This paper cites AI and Deep Learning for Terahertz Ultra-Massive MIMO: From Model-Driven Approaches to Foundation Models.

A look at adversarial attacks on radio waveforms from discrete latent space AI and Deep Learning for Terahertz Ultra-Massive MIMO: From Model-Driven Approaches to Foundation Models

Reference 10

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Source-reported events for the cited work

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Observation 89890d0d-3203-45de-ab2a-e6e16ae58f46 · outbound

This paper cites Generative Diffusion Models for High Dimensional Channel Estimation,.

A look at adversarial attacks on radio waveforms from discrete latent space Generative Diffusion Models for High Dimensional Channel Estimation,

Reference 11

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Source-reported events for the cited work

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Observation 7a43c5fb-ec1a-4c55-a9cb-da1319323cf2 · outbound

This paper cites Intriguing properties of neural networks.

A look at adversarial attacks on radio waveforms from discrete latent space Intriguing properties of neural networks

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f7af301a-8119-4a99-a1d5-2e2f930e1680 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

A look at adversarial attacks on radio waveforms from discrete latent space Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fc230689-2a85-4655-a789-6c2fa1d6ac6f · outbound

This paper cites Large Scale Radio Frequency Signal Classification,.

A look at adversarial attacks on radio waveforms from discrete latent space Large Scale Radio Frequency Signal Classification,

Reference 14

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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 0c793ade-f383-4c32-a460-ee57415e64c3 · outbound

This paper cites Back to single-carrier for beyond-5g communications above 90ghz: Novel index modulation techniques for low-power wireless terabits system in sub-thz bands,.

A look at adversarial attacks on radio waveforms from discrete latent space Back to single-carrier for beyond-5g communications above 90ghz: Novel index modulation techniques for low-power wireless terabits system in sub-thz bands,

Reference 15

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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 c955ae4d-53d4-44df-8e3e-50d3e7e31e17 · outbound

This paper cites Wireless backhaul in 5g and beyond: Issues, challenges and opportunities,.

A look at adversarial attacks on radio waveforms from discrete latent space Wireless backhaul in 5g and beyond: Issues, challenges and opportunities,

Reference 16

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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 4ef6a347-a2f1-4586-bf2d-0cb4896b0be2 · outbound

This paper cites Optimizing mmwave wireless backhaul schedul- ing,.

A look at adversarial attacks on radio waveforms from discrete latent space Optimizing mmwave wireless backhaul schedul- ing,

Reference 17

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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 fbce4da0-d7df-43c4-a108-3c376486efe6 · outbound

This paper cites Neural discrete representation learning,.

A look at adversarial attacks on radio waveforms from discrete latent space Neural discrete representation learning,

Reference 18

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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 289ca72a-8663-45d7-b57c-9e0d9f2062be · outbound

This paper cites Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks,.

A look at adversarial attacks on radio waveforms from discrete latent space Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks,

Reference 19

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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 5f9ad075-e8bb-4cea-8cb5-bbe76c11f4bc · outbound

This paper cites SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantization.

A look at adversarial attacks on radio waveforms from discrete latent space SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantization

Reference 20

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Source-reported events for the cited work

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Observation 3d8aa012-b939-4817-a95a-a4c61ca66234 · outbound

This paper cites Combatting adversarial attacks through denoising and dimensionality reduction: A cascaded autoencoder approach,.

A look at adversarial attacks on radio waveforms from discrete latent space Combatting adversarial attacks through denoising and dimensionality reduction: A cascaded autoencoder approach,

Reference 21

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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 1117388c-f660-4c73-b9f9-745549bf10d6 · outbound

This paper cites Large Scale Radio Frequency Signal Classification.

A look at adversarial attacks on radio waveforms from discrete latent space Large Scale Radio Frequency Signal Classification

Reference 2022

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.