Paper Citation Record · LEDGER

Automatic Modulation Classification via Green Machine Learning

As of 5 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2604.10317.

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

pith.paper-citation-record.v1
2604.10317 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:30:00.635464Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:00:12.251666Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

verified exact3
verified fuzzy44
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 872620b7-4e52-4be2-a96f-9d7e437d0334 · outbound

This paper cites Recent advances in automatic modulation classification technology: Methods, results, and prospects.

Automatic Modulation Classification via Green Machine Learning Recent advances in automatic modulation classification technology: Methods, results, and prospects

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.773379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fd588fbc-3f36-44ad-bd00-02a70792d26a · outbound

This paper cites Automatic modulation classification of digital communication signals using svm based on hybrid features, cyclostationary, and information entropy.

Automatic Modulation Classification via Green Machine Learning Automatic modulation classification of digital communication signals using svm based on hybrid features, cyclostationary, and information entropy

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.770009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4c949e72-5956-4d40-9347-0025ce235a58 · outbound

This paper cites Maximum-likelihood classification for digital amplitude-phase modulations.

Automatic Modulation Classification via Green Machine Learning Maximum-likelihood classification for digital amplitude-phase modulations

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.739164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f4fa5519-0efd-4ea0-8aff-2d211cb1782a · outbound

This paper cites Multitask-learning- based deep neural network for automatic modulation classification.

Automatic Modulation Classification via Green Machine Learning Multitask-learning- based deep neural network for automatic modulation classification

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.744360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 19dc142e-1806-4bfe-8247-e16d54c1b656 · outbound

This paper cites Maximum-likelihood modulation classification for psk/qam.

Automatic Modulation Classification via Green Machine Learning Maximum-likelihood modulation classification for psk/qam

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.741755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fd83e914-3812-4814-98ba-b133ffd22f34 · outbound

This paper cites Accuracy analysis of feature- based automatic modulation classification via deep neural network.

Automatic Modulation Classification via Green Machine Learning Accuracy analysis of feature- based automatic modulation classification via deep neural network

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.733926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 15d7c73b-47b7-4a7a-a756-cf81a44a700c · outbound

This paper cites Automatic modulation classification using moments and likelihood maximization.

Automatic Modulation Classification via Green Machine Learning Automatic modulation classification using moments and likelihood maximization

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.748115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1cbe0ccd-5761-46e8-9d17-d91bc3936576 · outbound

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

Automatic Modulation Classification via Green Machine Learning Novel automatic modulation classification using cumulant features for communications via multipath channels

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.720409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 12f6b0e7-1289-4795-a016-e4154fcdc82e · outbound

This paper cites Automatic modulation classification for cognitive radios using cyclic feature detection.

Automatic Modulation Classification via Green Machine Learning Automatic modulation classification for cognitive radios using cyclic feature detection

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.706475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b9d7e649-f098-4ccd-9b8f-baf412e5411a · outbound

This paper cites Automatic mod- ulation classification using convolutional neural network with features fusion of spwvd and bjd.

Automatic Modulation Classification via Green Machine Learning Automatic mod- ulation classification using convolutional neural network with features fusion of spwvd and bjd

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.730205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 64e8fbd2-bd9a-4134-bcfd-38561aae7b0f · outbound

This paper cites Graphic constellations and dbn based automatic modulation classification.

Automatic Modulation Classification via Green Machine Learning Graphic constellations and dbn based automatic modulation classification

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.736182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0f444be5-90d7-4f31-9fe0-b78be3d5c40f · outbound

This paper cites Genetic algorithm optimized distribution sampling test for m-qam modulation classification.

Automatic Modulation Classification via Green Machine Learning Genetic algorithm optimized distribution sampling test for m-qam modulation classification

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.738906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3496496c-8d18-436e-ae87-d9b3e84ec576 · outbound

This paper cites Fast and robust modulation classification via kolmogorov-smirnov test.

Automatic Modulation Classification via Green Machine Learning Fast and robust modulation classification via kolmogorov-smirnov test

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.731410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 97c46fe9-b0eb-447b-8f16-9c6f63f479fd · outbound

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

Automatic Modulation Classification via Green Machine Learning Over-the-air deep learning based radio signal classification

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.760480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2830429f-e989-4809-bbf5-c49c0400922b · outbound

This paper cites Mobilerat: a lightweight radio transformer method for automatic modulation classification in drone communication systems.

Automatic Modulation Classification via Green Machine Learning Mobilerat: a lightweight radio transformer method for automatic modulation classification in drone communication systems

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.726024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1ee3352b-f7da-4668-b47d-cabb919233d1 · outbound

This paper cites Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels.

Automatic Modulation Classification via Green Machine Learning Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:26:00.757601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3cda56aa-34cf-4847-a051-66fa86aa2061 · outbound

This paper cites G-amc: A green automatic modulation classification method.

Automatic Modulation Classification via Green Machine Learning G-amc: A green automatic modulation classification method

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.712155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a4d28caa-d510-4c6c-b184-7be6ccd742e7 · outbound

This paper cites Performance evaluation of feature-based automatic modulation classification.

Automatic Modulation Classification via Green Machine Learning Performance evaluation of feature-based automatic modulation classification

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.718726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7d83072a-d70c-4f14-ab01-6eb7bd0745f6 · outbound

This paper cites Modulation classification in multipath fading channels using sixth-order cumulants and stacked convolutional auto-encoders.

Automatic Modulation Classification via Green Machine Learning Modulation classification in multipath fading channels using sixth-order cumulants and stacked convolutional auto-encoders

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.728618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 727265c7-89c0-4a19-92f4-d90dbcc38be4 · outbound

This paper cites Deep neural network architectures for modulation classification.

Automatic Modulation Classification via Green Machine Learning Deep neural network architectures for modulation classification

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.736408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a3eb538f-34de-4bcd-b448-39a6b73485e9 · outbound

This paper cites Deep learning models for wireless signal classification with distributed low- cost spectrum sensors.

Automatic Modulation Classification via Green Machine Learning Deep learning models for wireless signal classification with distributed low- cost spectrum sensors

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.757421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a0275a58-b822-456b-bade-999454d81470 · outbound

This paper cites Radio modulation classification using deep learning architectures.

Automatic Modulation Classification via Green Machine Learning Radio modulation classification using deep learning architectures

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.754222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a0afcdcc-ea98-48ba-b637-a1fbecbfc611 · outbound

This paper cites Intra-pulse modulation radar signal recognition based on cldn network.

Automatic Modulation Classification via Green Machine Learning Intra-pulse modulation radar signal recognition based on cldn network

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.695063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b2facf0d-df7c-4a34-9bc5-d0ba9c02e1b3 · outbound

This paper cites Deep multi-scale representation learning with attention for automatic modulation classification.

Automatic Modulation Classification via Green Machine Learning Deep multi-scale representation learning with attention for automatic modulation classification

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.692526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2f924fe7-08b1-4b44-a7b8-8a32fd6feb9f · outbound

This paper cites Automatic modulation classification with deep neural networks.

Automatic Modulation Classification via Green Machine Learning Automatic modulation classification with deep neural networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.700499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 681ba0c7-7520-43aa-9d67-b4d983bf52d4 · outbound

This paper cites Spectrum interference- based two-level data augmentation method in deep learning for auto- matic modulation classification.

Automatic Modulation Classification via Green Machine Learning Spectrum interference- based two-level data augmentation method in deep learning for auto- matic modulation classification

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.703537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation eb0bc521-16cf-40c7-b9f0-af90a318f030 · outbound

This paper cites Dl-pr: Generalized automatic modulation classification method based on deep learning with priori regularization.

Automatic Modulation Classification via Green Machine Learning Dl-pr: Generalized automatic modulation classification method based on deep learning with priori regularization

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.766578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c033c0a3-9b72-4682-b2e4-11ddd1311d55 · outbound

This paper cites Efficient automatic modulation classification for next-generation wireless networks.

Automatic Modulation Classification via Green Machine Learning Efficient automatic modulation classification for next-generation wireless networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.687195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ea06e383-c665-4b6b-be89-a063ddf16413 · outbound

This paper cites Kadnet: Low snr automatic modulation classification via snr aware deformable convolu- tion and kolmogorov–arnold networks.

Automatic Modulation Classification via Green Machine Learning Kadnet: Low snr automatic modulation classification via snr aware deformable convolu- tion and kolmogorov–arnold networks

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.689997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3010472a-0e13-4764-be83-7b3226515ac8 · outbound

This paper cites Hfdnn: A hybrid fusion deep neural network for robust automatic mod- ulation classification in adverse wireless environments.

Automatic Modulation Classification via Green Machine Learning Hfdnn: A hybrid fusion deep neural network for robust automatic mod- ulation classification in adverse wireless environments

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.709389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e5e7462b-8e93-493e-a68a-2c7f9a8518be · outbound

This paper cites Mcformer: A transformer based deep neural network for automatic modulation classification.

Automatic Modulation Classification via Green Machine Learning Mcformer: A transformer based deep neural network for automatic modulation classification

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.763278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 779066ca-d020-4870-8626-b66cb59d86c7 · outbound

This paper cites Fine-grained modulation classification using multi-scale radio trans- former with dual-channel representation.

Automatic Modulation Classification via Green Machine Learning Fine-grained modulation classification using multi-scale radio trans- former with dual-channel representation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.750978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 14d87e20-dfd9-40a1-9360-0d5242ea1852 · outbound

This paper cites MoE-AMC: Enhancing Automatic Modulation Classification Performance Using Mixture-of-Experts.

Automatic Modulation Classification via Green Machine Learning MoE-AMC: Enhancing Automatic Modulation Classification Performance Using Mixture-of-Experts

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:26:00.748014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation dbd1b26d-28de-46d7-852e-9c70c5b31c88 · outbound

This paper cites Adversarial attack and reliable defense based on frequency domain feature enhance- ment for automatic modulation classification.

Automatic Modulation Classification via Green Machine Learning Adversarial attack and reliable defense based on frequency domain feature enhance- ment for automatic modulation classification

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.688953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3322e6a7-1454-4626-93a7-45e1e4c2245e · outbound

This paper cites Attention-enhanced hybrid automatic modulation classification for advanced wireless communication systems: A deep learning-transformer framework.

Automatic Modulation Classification via Green Machine Learning Attention-enhanced hybrid automatic modulation classification for advanced wireless communication systems: A deep learning-transformer framework

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.681203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bd76852a-267a-40b3-addb-75dd4c255251 · outbound

This paper cites Avgnet: Adaptive visibility graph neural network and its application in modulation classification.

Automatic Modulation Classification via Green Machine Learning Avgnet: Adaptive visibility graph neural network and its application in modulation classification

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.667888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 800eb79a-ae70-4f47-bed4-c4c58dbf920c · outbound

This paper cites Automatic mod- ulation classification based on cnn-transformer graph neural network.

Automatic Modulation Classification via Green Machine Learning Automatic mod- ulation classification based on cnn-transformer graph neural network

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.670590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation dc422e7d-1068-4462-9a9e-47544788fc4e · outbound

This paper cites Deep learning-based robust automatic modulation classification for cognitive radio networks.

Automatic Modulation Classification via Green Machine Learning Deep learning-based robust automatic modulation classification for cognitive radio networks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.649461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4dd68778-5d7e-41dc-a39b-a649e4232a15 · outbound

This paper cites Xgboost: A scalable tree boosting system.

Automatic Modulation Classification via Green Machine Learning Xgboost: A scalable tree boosting system

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.678425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b46312c4-61c9-4070-9784-1645d0bcf90f · outbound

This paper cites A statistics- based feature generation (sfg) method: Theory and applications.

Automatic Modulation Classification via Green Machine Learning A statistics- based feature generation (sfg) method: Theory and applications

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.676055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f4037b36-0b73-409e-9e79-d4aa9288408a · outbound

This paper cites Radioml2016.10a/10b/10c.

Automatic Modulation Classification via Green Machine Learning Radioml2016.10a/10b/10c

Reference 41

Resolution: verified exact; doi, observed 2026-05-10T15:30:32.026607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6e90d929-c32b-4d63-b734-cb812456f5ea · outbound

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

Automatic Modulation Classification via Green Machine Learning A spatiotemporal multi-channel learning framework for automatic modulation recognition

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.664891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a30be2d8-1bb1-4df1-8715-7b7ff87bdef5 · outbound

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

Automatic Modulation Classification via Green Machine Learning An efficient deep learning model for automatic modulation recognition based on parameter estimation and transformation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.675603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3d1a7ea3-7564-4d29-981f-8f7b15c7a130 · outbound

This paper cites A family of automatic modulation classification models based on domain knowledge for various platforms.

Automatic Modulation Classification via Green Machine Learning A family of automatic modulation classification models based on domain knowledge for various platforms

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.680666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a3d8a67e-2588-4f73-ab6e-0227aa38610f · outbound

This paper cites Mobileamct: A lightweight mobile automatic modulation classification transformer in drone communication systems.

Automatic Modulation Classification via Green Machine Learning Mobileamct: A lightweight mobile automatic modulation classification transformer in drone communication systems

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.665202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation daede0fd-ee06-4c88-aa3c-36f48440129c · outbound

This paper cites Abftnet: An efficient transformer network with alignment before fusion for multimodal automatic modulation recognition.

Automatic Modulation Classification via Green Machine Learning Abftnet: An efficient transformer network with alignment before fusion for multimodal automatic modulation recognition

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.684539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation aaf15126-2ea3-47cb-92c6-a4a5ee57f63c · outbound

This paper cites Gignet: A graph- in-graph neural network for automatic modulation recognition.

Automatic Modulation Classification via Green Machine Learning Gignet: A graph- in-graph neural network for automatic modulation recognition

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T21:52:08.683267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Pith citing papers

Observation 051834ee-1687-410f-bec6-157eb297ce26 · inbound

Cross-Fitted Residual Utility for Primary-Preserving Cognitive Decision Correction in Automatic Modulation Classification cites this paper.

Cross-Fitted Residual Utility for Primary-Preserving Cognitive Decision Correction in Automatic Modulation Classification Automatic Modulation Classification via Green Machine Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T16:00:12.251666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.