Paper Citation Record · LEDGER

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models

As of 18 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2508.01719.

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

pith.paper-citation-record.v1
2508.01719 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:31:49.540652Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

40 of 40 outbound references displayed

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verified fuzzy36
unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4c00bd51-8586-4d1a-a5ff-cfa30c11bee2 · outbound

This paper cites Lightweight automatic modulation classification via progres- sive differentiable architecture search,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Lightweight automatic modulation classification via progres- sive differentiable architecture search,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.876039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 923a1891-1f16-4ef5-9471-3c9f94623d1a · outbound

This paper cites Novel automatic modulation classification using cumulant features for communications via multipath channels,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Novel automatic modulation classification using cumulant features for communications via multipath channels,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.868572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad79f010-7e30-41ce-887d-854f0d20cee5 · outbound

This paper cites Psrnet: Few-shot automatic modulation classification under potential domain differences,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Psrnet: Few-shot automatic modulation classification under potential domain differences,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.860804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3e6821b3-b1f0-4059-9812-e8d61dda10aa · outbound

This paper cites Shared spectrum monitoring using deep learning,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Shared spectrum monitoring using deep learning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.852194Z

Source-reported events for the cited work

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Observation cec52d03-60e4-4572-9711-f29bb95798c1 · outbound

This paper cites Pass-net: A pseudo classes and stochastic classifiers based network for few-shot class-incremental automatic modulation classification,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Pass-net: A pseudo classes and stochastic classifiers based network for few-shot class-incremental automatic modulation classification,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.844456Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 88929cb0-2b44-4115-b93a-d738f6720761 · outbound

This paper cites Ofdm receiver design with learning-driven automatic modulation recognition,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Ofdm receiver design with learning-driven automatic modulation recognition,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.836918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7d0186e5-bfef-48e0-a76f-de125f689805 · outbound

This paper cites One2threenet: An automatic microscale-based modulation recognition method for underwater acous- tic communication systems,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models One2threenet: An automatic microscale-based modulation recognition method for underwater acous- tic communication systems,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.829089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f8cd7f56-24ff-4f89-a1e8-735a9f0b02bc · outbound

This paper cites Afd-il: A long- term incremental learning approach with adaptive feature distillation for specific emitter identification,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Afd-il: A long- term incremental learning approach with adaptive feature distillation for specific emitter identification,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.821193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0aa24140-0ee2-493d-96e7-a40ccad53fb3 · outbound

This paper cites Multi-scale feature fusion and distribution similarity network for few-shot automatic modulation classification,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Multi-scale feature fusion and distribution similarity network for few-shot automatic modulation classification,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.813027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 52eb4d70-d2bc-435c-84aa-4828fa4d6883 · outbound

This paper cites A survey of deep transfer learning in automatic modulation classification,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models A survey of deep transfer learning in automatic modulation classification,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.804365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad1c8a67-2162-46a0-bbd4-055fbd92b592 · outbound

This paper cites A transformer-based contrastive semi-supervised learning framework for automatic modula- tion recognition,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models A transformer-based contrastive semi-supervised learning framework for automatic modula- tion recognition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.796181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 173b8340-374e-4a27-874e-96249d96bdf5 · outbound

This paper cites MCLHN: Toward automatic modulation classification via masked contrastive learning with hard negatives,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models MCLHN: Toward automatic modulation classification via masked contrastive learning with hard negatives,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.787725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation de671dd2-6286-4f7c-a5cb-a602e791598d · outbound

This paper cites Unsupervised modulation recognition method based on multi-domain representation contrastive learning,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Unsupervised modulation recognition method based on multi-domain representation contrastive learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.779855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 872ba783-983b-481f-8c85-34578baa5e80 · outbound

This paper cites Auto-encoding variational bayes,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Auto-encoding variational bayes,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.771382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6d06ac73-b074-424a-a0f7-5a0857fd4273 · outbound

This paper cites Generative adversarial nets,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Generative adversarial nets,

Reference 15

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Source-reported events for the cited work

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Observation 296bbb3d-1c1b-4be0-a7ea-eaf391356b8c · outbound

This paper cites Data augmentation aided automatic modulation recognition using diffusion model,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Data augmentation aided automatic modulation recognition using diffusion model,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.758712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eb7915d4-7ac8-4aa8-b38e-2949fe92f63d · outbound

This paper cites Diffusion model empowered data augmentation for automatic modulation recognition,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Diffusion model empowered data augmentation for automatic modulation recognition,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.751083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5220cb1b-1cd5-408f-b962-4eeebc2188a7 · outbound

This paper cites Denoising Diffusion Implicit Models.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Denoising Diffusion Implicit Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T05:31:49.485148Z

Source-reported events for the cited work

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Observation 8aa133f6-b535-4f58-80f8-e86dbac8e671 · outbound

This paper cites Denoising diffusion autoencoders are unified self-supervised learners,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Denoising diffusion autoencoders are unified self-supervised learners,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.743345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b6e99eeb-ebc5-4368-8357-338d99a32955 · outbound

This paper cites Diffusion model as representation learner,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Diffusion model as representation learner,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.735631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ff20eee0-32c9-44c5-8155-147dc9aba954 · outbound

This paper cites A contrastive learner for automatic modu- lation classification,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models A contrastive learner for automatic modu- lation classification,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.728336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4e3d5569-30e4-4580-abdd-c515ed6f4a13 · outbound

This paper cites Gaf-mae: A self- supervised automatic modulation classification method based on gramian angular field and masked autoencoder,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Gaf-mae: A self- supervised automatic modulation classification method based on gramian angular field and masked autoencoder,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.720552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b7c9e7df-5661-49bc-b97e-6c08e09b1402 · outbound

This paper cites Over-the-air deep learnig based radio signal classification,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Over-the-air deep learnig based radio signal classification,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.712818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f07e0c3a-13ed-4a97-b1e6-c3e1190c397f · outbound

This paper cites Deep neural network architectures for modulation classification,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Deep neural network architectures for modulation classification,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.705044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c9f7fab7-e265-48ef-a7c5-20398d0189fb · outbound

This paper cites Real-time radio technology and modulation classification via an lstm auto-encoder,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Real-time radio technology and modulation classification via an lstm auto-encoder,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.697693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a6f63565-4e40-4bf5-9f85-68c7dc8a60d3 · outbound

This paper cites A spatiotemporal multi-channel learning framework for automatic modulation recognition,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models A spatiotemporal multi-channel learning framework for automatic modulation recognition,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.689603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a42e1765-9e2d-4278-8a4e-54e9655de633 · outbound

This paper cites Automatic modulation classification based on complex-valued convolutional neural network and semi-supervised learning,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Automatic modulation classification based on complex-valued convolutional neural network and semi-supervised learning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.681252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 45d7076b-3a60-4461-b80b-8b617ff56f84 · outbound

This paper cites A transformer-based CTDNN structure for automatic modulation recognition,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models A transformer-based CTDNN structure for automatic modulation recognition,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.672982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9b908160-bd61-4b0e-9b50-3ddbb35d2cac · outbound

This paper cites Self-contrastive learning based semi-supervised radio modulation classification,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Self-contrastive learning based semi-supervised radio modulation classification,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.665130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 52891ba2-21da-4e57-b62b-a3572b7b4343 · outbound

This paper cites Hybrid-view self- supervised framework for automatic modulation recognition,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Hybrid-view self- supervised framework for automatic modulation recognition,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.656731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 38067507-7209-40eb-ad3b-97ddc555b9ce · outbound

This paper cites Multi- representation domain attentive contrastive learning based unsupervised automatic modulation recognition,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Multi- representation domain attentive contrastive learning based unsupervised automatic modulation recognition,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.648527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 92138e26-f163-4ca8-8f61-7a8afa069157 · outbound

This paper cites Video diffusion models,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Video diffusion models,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T05:31:49.520428Z

Source-reported events for the cited work

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Observation 624eced1-05b2-4867-9b9c-148fea1b48c7 · outbound

This paper cites Radio machine learning dataset generation with gnu radio,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Radio machine learning dataset generation with gnu radio,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.634909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7425bfe8-bb37-41a9-b4b4-9eef6f2cec16 · outbound

This paper cites Convolutional radio mod- ulation recognition networks,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Convolutional radio mod- ulation recognition networks,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.626473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 28bf5f01-ba1f-44be-ae09-d5beab4e3e0d · outbound

This paper cites RML22: Realistic dataset generation for wireless modulation classification,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models RML22: Realistic dataset generation for wireless modulation classification,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.617833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a4e1b81b-6d2e-4074-813e-f1c7efd12ea0 · outbound

This paper cites An efficient deep learning model for automatic modulation recognition based on parameter estimation and transformation,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models An efficient deep learning model for automatic modulation recognition based on parameter estimation and transformation,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.609743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d6626d8a-c705-466a-8695-51678467820a · outbound

This paper cites Open set recognition of communication signal modulation based on deep learning,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Open set recognition of communication signal modulation based on deep learning,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.601575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 973ed4ac-b5f2-4172-95e3-5d9868cca832 · outbound

This paper cites OSMR: Open- set modulation recognition based on information enhancement,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models OSMR: Open- set modulation recognition based on information enhancement,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.593606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 121982e0-dac1-47e5-b5d7-413881b1912c · outbound

This paper cites SSRCNN: A semi-supervised Learning framework for signal recognition,.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models SSRCNN: A semi-supervised Learning framework for signal recognition,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:31:49.584872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 296ef9f1-5651-44ed-8bcd-8e78715e71eb · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models Representation Learning with Contrastive Predictive Coding

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T05:31:49.540652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

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