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Paper Citation Record · LEDGER

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2510.09405.

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

pith.paper-citation-record.v1
2510.09405 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T10:39:49.585089Z

measured 36 of 36 standing notices

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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.

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measured 0 of 1 external citation measurements

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

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Reference resolution

36 of 36 outbound references displayed

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Outbound references

Observation c4cee756-edeb-4fe6-82ce-1f4acfaf25b6 · outbound

This paper cites Internet of vehicles in big data era,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Internet of vehicles in big data era,

Reference 1

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Observation f37574f6-77b0-4b2f-ae36-84bedea1d35b · outbound

This paper cites Connected vehicles: Solutions and challenges,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Connected vehicles: Solutions and challenges,

Reference 2

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Observation 17acb9f0-a7f6-4e3d-8094-e523bcc109c6 · outbound

This paper cites Specific emitter identification based on hilbert–huang transform-based time–frequency–energy distri- bution features,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Specific emitter identification based on hilbert–huang transform-based time–frequency–energy distri- bution features,

Reference 3

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Observation 89f9bd86-b868-41de-9765-88e2fefd9a64 · outbound

This paper cites Specific emitter identifica- tion via convolutional neural networks,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Specific emitter identifica- tion via convolutional neural networks,

Reference 4

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Observation 03c9d570-ae81-4aa3-98e0-c9bfcb7b0cc5 · outbound

This paper cites Deep learning based rf fingerprint identification using differential constellation trace figure,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Deep learning based rf fingerprint identification using differential constellation trace figure,

Reference 5

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Observation e2ddae5b-3137-450a-97cc-88706c8fe78d · outbound

This paper cites Multimodal sparse representation-based classification scheme for rf fingerprinting,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Multimodal sparse representation-based classification scheme for rf fingerprinting,

Reference 6

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Observation 59868c64-6a23-41f2-bd4e-12ec8a0e60bd · outbound

This paper cites Accurate and effi- cient wireless device fingerprinting using channel state information,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Accurate and effi- cient wireless device fingerprinting using channel state information,

Reference 7

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source=pdf_text observed=2026-08-04T10:39:46.760766Z digest=sha256:2ff800a202b2b8b11bf0c956bd9682e2b6118923fb1ff5b8afde002130dbe7dc

Observation aea563a9-0d41-46d0-b543-4f4fce129ec2 · outbound

This paper cites Radio fre- quency fingerprint identification for lora using spectrogram and cnn,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Radio fre- quency fingerprint identification for lora using spectrogram and cnn,

Reference 8

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Observation 06bd13d8-4696-4aab-8c7a-7cb21023ef42 · outbound

This paper cites Robust wireless fin- gerprinting via complex-valued neural networks,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Robust wireless fin- gerprinting via complex-valued neural networks,

Reference 9

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source=pdf_text observed=2026-08-04T10:39:47.047303Z digest=sha256:a4cd7604000b26b2cfad0fdec0f396dc75c755b6d8981ea0354e3e71103b7d24

Observation bfe4bee7-39f3-4657-b3d3-45953195a889 · outbound

This paper cites Ex- posing the fingerprint: Dissecting the impact of the wireless channel on radio fingerprinting,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Ex- posing the fingerprint: Dissecting the impact of the wireless channel on radio fingerprinting,

Reference 10

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source=pdf_text observed=2026-08-04T10:39:47.134444Z digest=sha256:95c71c8aa61a3ab96e9e88f025981388f4e9e56129d9b857f058ca1ce27286e0

Observation dad24c21-4cee-4309-8cbd-92ca626f4d57 · outbound

This paper cites Radiodiff: An effective generative diffusion model for sampling-free dynamic radio map construction,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Radiodiff: An effective generative diffusion model for sampling-free dynamic radio map construction,

Reference 11

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source=pdf_text observed=2026-08-04T10:39:47.236069Z digest=sha256:4e2fc4984f037180f97f822b2f564424783ff004a40b56aa928171d15ff93db5

Observation 36c24282-7c84-448b-b197-1f5a08aa367b · outbound

This paper cites Radiodiff-k 2: Helmholtz equation informed generative diffu- sion model for multipath-aware radio map construction,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Radiodiff-k 2: Helmholtz equation informed generative diffu- sion model for multipath-aware radio map construction,

Reference 12

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source=pdf_text observed=2026-08-04T10:39:47.315871Z digest=sha256:8a4fda859dc4d6b3fca481ad8b61de809eedbb5f1ffdd6bd3a6aa236cd272dda

Observation e5ed9435-46b2-4600-8c84-5b1bd487f306 · outbound

This paper cites Oracle: Optimized radio classification through convo- lutional neural networks,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Oracle: Optimized radio classification through convo- lutional neural networks,

Reference 13

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Observation f49d00d4-ad7f-4035-88dc-cb2bf4a01423 · outbound

This paper cites Towards scalable and channel-robust radio frequency fingerprint identification for lora,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Towards scalable and channel-robust radio frequency fingerprint identification for lora,

Reference 14

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source=pdf_text observed=2026-08-04T10:39:47.535393Z digest=sha256:a6c5a4e7af3d3f9e1dc5dd917705e273d207f7c2935dcf0c54d402c98c5ec8f7

Observation bcc108ed-cac8-474c-8798-a93a01bdf683 · outbound

This paper cites Wisig: A large-scale wifi signal dataset for receiver and channel agnostic rf fingerprinting,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Wisig: A large-scale wifi signal dataset for receiver and channel agnostic rf fingerprinting,

Reference 15

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source=pdf_text observed=2026-08-04T10:39:47.631936Z digest=sha256:4358ecc5f06ec63e201a972b9228c70a7bdc01851dc827806964e557feaf9f91

Observation f3189f8b-974e-4cac-98cb-01083bdff1eb · outbound

This paper cites A deep learning approach to iot authentication,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training A deep learning approach to iot authentication,

Reference 16

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source=pdf_text observed=2026-08-04T10:39:47.730962Z digest=sha256:b737822c03112c807641efa54f2d70e541e91625c1e2c8814fb4b12c045ae28c

Observation 5006e71e-05b8-42cb-83d4-795f7b8b4c12 · outbound

This paper cites Deep learning for rf device fingerprinting in cognitive communication networks,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Deep learning for rf device fingerprinting in cognitive communication networks,

Reference 17

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source=pdf_text observed=2026-08-04T10:39:47.826822Z digest=sha256:05094393df03be90f7a3ffec942437ef75323b6d292ee28dfde84989da9a36ff

Observation 8da13b9f-da55-4905-ae43-be275a64c8e5 · outbound

This paper cites Adaptive rf fingerprints fusion via dual attention convolutions,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Adaptive rf fingerprints fusion via dual attention convolutions,

Reference 18

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source=pdf_text observed=2026-08-04T10:39:47.904029Z digest=sha256:7a00333968eb76e71fbec71b26bc4763d02774f80eba6e1c88acc5d2aa02f181

Observation 574cde77-4c5d-4f35-8fc4-930a5b90f1db · outbound

This paper cites Toward length-versatile and noise-robust radio frequency fingerprint identification,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Toward length-versatile and noise-robust radio frequency fingerprint identification,

Reference 19

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source=pdf_text observed=2026-08-04T10:39:47.988245Z digest=sha256:212aec9a3bc4148f73b597165274244be6acff4e85e1e2b3ea75397a847b34da

Observation 21826c1c-ddce-4edf-9821-ae153f33d0d1 · outbound

This paper cites Multi-channel attentive feature fusion for radio frequency fingerprinting,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Multi-channel attentive feature fusion for radio frequency fingerprinting,

Reference 20

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Observation 61a89a44-bf4b-44a5-8c50-3aa2b0c2613b · outbound

This paper cites Equalization assisted domain adaptation for radio frequency fingerprint identification,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Equalization assisted domain adaptation for radio frequency fingerprint identification,

Reference 21

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Observation 4c6e7797-2b02-42dd-965b-81fb58363373 · outbound

This paper cites Channel-robust rf fingerprint identification using multi-task learning and receiver collabo- ration,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Channel-robust rf fingerprint identification using multi-task learning and receiver collabo- ration,

Reference 22

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source=pdf_text observed=2026-08-04T10:39:48.274352Z digest=sha256:3261b4f5689e69904f439886f2f427e0478d5c9353793803ca87c1e0a107a309

Observation 257c6896-dec2-49d6-bb5f-7f0007c591c4 · outbound

This paper cites Prototype- driven unsupervised domain adaptation for specific emitter identifica- tion,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Prototype- driven unsupervised domain adaptation for specific emitter identifica- tion,

Reference 23

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Observation f059ce2d-eecb-46a9-bb72-f1a19f167d7c · outbound

This paper cites Cross-domain, scalable, and in- terpretable rf device fingerprinting,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Cross-domain, scalable, and in- terpretable rf device fingerprinting,

Reference 24

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Observation 49fe8007-74b6-415c-ab43-a218b6b5c856 · outbound

This paper cites Vc-sei: Robust variable-channel specific emitter identification method using semi-supervised domain adaptation,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Vc-sei: Robust variable-channel specific emitter identification method using semi-supervised domain adaptation,

Reference 25

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source=pdf_text observed=2026-08-04T10:39:48.561441Z digest=sha256:bcdd8ecf93ffdab1f60d53779642e0598ee46729b187b3616222da434dcdffc8

Observation a63c283a-61db-408b-9d7a-db3e0ae5c024 · outbound

This paper cites Cross-receiver radio frequency fingerprint identification based on contrastive learning and subdomain adaptation,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Cross-receiver radio frequency fingerprint identification based on contrastive learning and subdomain adaptation,

Reference 26

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source=pdf_text observed=2026-08-04T10:39:48.663550Z digest=sha256:983f625dc7ff88610549adf4569a951831d28c427d971b7bb9661c40d35437e6

Observation 93aaf509-6dcb-4c2e-aba6-dd3c0b137493 · outbound

This paper cites Cross-device radio frequency fingerprinting identification based on do- main adaptation,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Cross-device radio frequency fingerprinting identification based on do- main adaptation,

Reference 27

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Observation a4df49fa-a7d1-410f-97b6-b0092cd0d18a · outbound

This paper cites Avoiding shortcuts: Enhancing channel-robust specific emitter identification via single-source domain generalization,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Avoiding shortcuts: Enhancing channel-robust specific emitter identification via single-source domain generalization,

Reference 28

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Observation f2c05751-37ab-4a6e-890b-4ccb19753822 · outbound

This paper cites Gan-rxa: A practical scalable solution to receiver-agnostic transmitter fingerprinting,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Gan-rxa: A practical scalable solution to receiver-agnostic transmitter fingerprinting,

Reference 29

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source=pdf_text observed=2026-08-04T10:39:48.926840Z digest=sha256:a3d4552bb0cdbef47fe0a89f56e9bd055acead8b9d05d888ed826b332d2a0972

Observation 12600096-c64d-45f7-a6f2-df7ce20d0aee · outbound

This paper cites Domain generaliza- tion for cross-receiver radio frequency fingerprint identification,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Domain generaliza- tion for cross-receiver radio frequency fingerprint identification,

Reference 30

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Observation ba3bbc1d-20ed-43eb-a08f-f71f899bc22d · outbound

This paper cites Detecting change in data streams,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Detecting change in data streams,

Reference 31

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Observation 293400e4-3d1e-4bdf-a11d-aa85867a7b92 · outbound

This paper cites Generalizing to unseen domains via distribution matching.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Generalizing to unseen domains via distribution matching

Reference 32

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Observation 549184ef-3524-4810-bdbe-67512aaeaaab · outbound

This paper cites On learning invariant representations for domain adaptation,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training On learning invariant representations for domain adaptation,

Reference 33

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Observation 39dfaedd-08f3-44a9-8b56-11d83fc91e89 · outbound

This paper cites A theory of learning from different domains,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training A theory of learning from different domains,

Reference 34

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Observation fe6ed427-398a-45ea-9c63-596e3641cba5 · outbound

This paper cites Deep residual learning for image recognition,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Deep residual learning for image recognition,

Reference 35

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Observation b7fd70b5-9a09-48a2-85fa-3344814f0ae0 · outbound

This paper cites Domain-adversarial training of neural networks,.

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training Domain-adversarial training of neural networks,

Reference 36

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source=pdf_text observed=2026-08-04T10:39:49.585089Z digest=sha256:05f75b2d7666ab59eb199a34d44f631fcec2418f7845db7eff31404db9a725e2

Pith citing papers

No inbound Pith citation observations are available.