Paper Citation Record · LEDGER

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels

As of 10 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2508.20193.

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

pith.paper-citation-record.v1
2508.20193 v2

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:17:51.526552Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T10:26:00.753110Z

Reference resolution

31 of 31 outbound references displayed

verified exact2
verified fuzzy28
unresolved1
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 654dce46-25b6-4ae2-8309-ad3d1ec22a53 · outbound

This paper cites A deep learning method based on convolutional neural network for automatic modulation classi- fication of wireless signals,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels A deep learning method based on convolutional neural network for automatic modulation classi- fication of wireless signals,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:52.110802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4c334d32-82f4-4865-9245-5218460e33ed · outbound

This paper cites Automatic mod- ulation classification using cnn with features fusion of spwvd and bjd,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Automatic mod- ulation classification using cnn with features fusion of spwvd and bjd,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:52.097546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2dab0c90-1c31-453d-a0e4-a1abf5c0e065 · outbound

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

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels A transformer-based contrastive semi-supervised learning framework for automatic modula- tionrecognition,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:52.084662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f7e60f73-73f4-4c71-9d5d-a537a4344f02 · outbound

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

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Over-the-air deep learning based radio signal classification,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:51.412020Z

Source-reported events for the cited work

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Observation 0d55d81a-b38b-4e2b-9793-fedca3840e6b · outbound

This paper cites Adversarial transfer learning for deep learning based automatic modulation classification,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Adversarial transfer learning for deep learning based automatic modulation classification,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:52.063498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0f6a4f00-f5b8-41fb-9671-a0cb0aba6362 · outbound

This paper cites Transfer learning for semi-supervised amc in zf-mimo systems,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Transfer learning for semi-supervised amc in zf-mimo systems,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:52.050838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 06087297-3d8a-413b-bed6-c3bbf159753b · outbound

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

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Self-contrastive learn- ing based semi-supervised radio modulation classification,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:52.038458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 163b1d1a-6d91-430e-a820-07466bfcd721 · outbound

This paper cites Semi-supervised modula- tion classification via an ensemble sigmatch method,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Semi-supervised modula- tion classification via an ensemble sigmatch method,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:52.024480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 021e43df-2acb-4238-9d35-88b81bc80684 · outbound

This paper cites Sscl-amc: A self-supervised automatic modulation classification method via dynamic augmentation and ensemble learning,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Sscl-amc: A self-supervised automatic modulation classification method via dynamic augmentation and ensemble learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:52.011188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bd2b5a38-3fd6-4307-a7ba-ffc01f634478 · outbound

This paper cites Modulation classification with data augmentation based on a semi-supervised generative model,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Modulation classification with data augmentation based on a semi-supervised generative model,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.997607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b16915b1-48be-476f-9ba8-c57c1eec55c5 · outbound

This paper cites Contrastive semi- supervised learning with pseudo-label for radar signal automatic mod- 21 ulation recognition,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Contrastive semi- supervised learning with pseudo-label for radar signal automatic mod- 21 ulation recognition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.985454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 42273395-255a-44aa-9358-986714cfd371 · outbound

This paper cites Augmented semi-supervised learning for cnn based automatic modulation classification,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Augmented semi-supervised learning for cnn based automatic modulation classification,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.973032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2094993f-d0ab-4f32-8a93-b74ead6cb591 · outbound

This paper cites Meta supervised contrastive learning for few-shot open-set modulation classification with signal con- stellation,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Meta supervised contrastive learning for few-shot open-set modulation classification with signal con- stellation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.958958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b2c20f33-6df6-4128-bd9a-e1cf5f3480ba · outbound

This paper cites Unsuper- visedtime-seriessignalanalysiswithautoencodersandvisiontransform- ers: A review of architectures and applications,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Unsuper- visedtime-seriessignalanalysiswithautoencodersandvisiontransform- ers: A review of architectures and applications,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.945648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c9e54dc8-cb94-4349-818c-1f23b46c0414 · outbound

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

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Gaf-mae: A self-supervised automatic modulation classification method based on gramian angular field and masked autoencoder,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.933359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7b556dd1-b451-417d-a848-12d3dd1864d9 · outbound

This paper cites Multiheart: Secure and ro- bust heartbeat pattern recognition in multimodal cardiac monitoring system,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Multiheart: Secure and ro- bust heartbeat pattern recognition in multimodal cardiac monitoring system,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.920739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b4099a09-2200-40b4-967c-efc882bb55d2 · outbound

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

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Spectrum interference-based two-level data augmentation method in deep learning for automatic modulation classification,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.907666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation de584b4b-89b5-4b5f-9fed-c5e8b4d8b13c · outbound

This paper cites Modulation classifier: A few-shot learning semi-supervised method based on multimodal infor- mation and domain adversarial network,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Modulation classifier: A few-shot learning semi-supervised method based on multimodal infor- mation and domain adversarial network,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.895207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 82a5acaf-c355-4a2d-8eb9-e413b015eda2 · outbound

This paper cites Soamc: A semi-supervised open-set recognition algorithm for automatic modulation classification,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Soamc: A semi-supervised open-set recognition algorithm for automatic modulation classification,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.882212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 75fcd687-f0c2-49f1-93f5-cef826f2915a · outbound

This paper cites Sanitizing Manufacturing Dataset Labels Using Vision-Language Models.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Sanitizing Manufacturing Dataset Labels Using Vision-Language Models

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d2279465-d3cf-44b4-84dc-caf07a451c56 · outbound

This paper cites Classimbalance-awareactivelearningwithvisiontransformersinfeder- ated histopathological imaging,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Classimbalance-awareactivelearningwithvisiontransformersinfeder- ated histopathological imaging,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.870918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2fe81260-f13e-4108-862c-964e2258cf8d · outbound

This paper cites Real-time wearable sensor compli- ance monitoring using a two-stage gradient-boosting classifier,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Real-time wearable sensor compli- ance monitoring using a two-stage gradient-boosting classifier,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.859994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 376063e3-c616-493c-9ffe-3b6416b69a44 · outbound

This paper cites Fine-grained open set signal modulation classification via self-supervised pre-training,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Fine-grained open set signal modulation classification via self-supervised pre-training,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.847899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 74d3fc20-24a7-49cc-a113-93ec72a59e43 · outbound

This paper cites A graph- based semi-supervised approach for few-shot class-incremental modula- tion classification,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels A graph- based semi-supervised approach for few-shot class-incremental modula- tion classification,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.836280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e411d1e1-59b6-4ae1-a6a0-53d129c77ab1 · outbound

This paper cites Network anomaly detection for iot using hyperdimensional computing on nsl-kdd,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Network anomaly detection for iot using hyperdimensional computing on nsl-kdd,

Reference 25

Resolution: verified exact; raw_fallback, observed 2026-08-05T15:17:51.729234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3d44c435-35fd-49d7-b54e-0f13796947c6 · outbound

This paper cites Msmcnet: A modular few-shot learning framework for signal modulation classification,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Msmcnet: A modular few-shot learning framework for signal modulation classification,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.822080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 67fcbcc2-b1eb-4b2d-87f3-7455482dbd39 · outbound

This paper cites A novel automatic modulation classification scheme based on multi-scale networks,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels A novel automatic modulation classification scheme based on multi-scale networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.808632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 852bf4d0-6dc5-4983-8099-82d3e3f03d90 · outbound

This paper cites Supervised ml method based modu- lation formats classification for wdm systems,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Supervised ml method based modu- lation formats classification for wdm systems,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.795084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 24c449a3-41fc-4141-9a4d-74a04bdcc927 · outbound

This paper cites Modulation format identification using su- pervised learning and high-dimensional features,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Modulation format identification using su- pervised learning and high-dimensional features,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.781407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5bdf3fd8-18aa-4d33-ab1e-c27121a4dbde · outbound

This paper cites Data augmentation for deep learning-based radio modulation classification,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Data augmentation for deep learning-based radio modulation classification,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.770030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f122505e-6db6-4aaf-8993-3774a43950ec · outbound

This paper cites Improving modulation recognition using time series data augmentation via a spatiotemporal multi-channel framework,.

Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labels Improving modulation recognition using time series data augmentation via a spatiotemporal multi-channel framework,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:51.758239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

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

Automatic Modulation Classification via Green Machine Learning cites this paper.

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 2026-08-10T06:31:04.303077+00:00.