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Paper Citation Record · LEDGER

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications

As of 15 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2508.19552.

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

pith.paper-citation-record.v1
2508.19552 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:45:18.184004Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

  • verified exact5
  • verified fuzzy28
  • unresolved5
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 54d4aa69-45b6-4bb8-8634-b90041045b6f · outbound

This paper cites GPT-4 Technical Report.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications GPT-4 Technical Report

Reference 1

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unresolved
no resolver link, observed 2026-08-05T15:45:17.988619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:45:17.988619Z digest=sha256:55faa61f7906f0282b39336ec6d6a54d8a3151738fe644115840a29887e096a5

Observation b0edda1b-fed6-467d-a285-4ffa177564a5 · outbound

This paper cites Deepseek-v3 technical report,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Deepseek-v3 technical report,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-05T15:45:20.076184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:17.994166Z digest=sha256:876775c48dfb1dd1dcb8575a480b1a96c16e2659bef7c2ffc0025582af8368a0

Observation 13942b72-09c7-494e-ab3f-635790585253 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 3

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no resolver link, observed 2026-08-05T15:45:18.005399Z

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source=pdf_text observed=2026-08-05T15:45:18.005399Z digest=sha256:0ec60f2e97a40d432b5ac6b05b33e4829dcdbcc1c0efa0bbff71033ea15a86dc

Observation 080a0026-a2ec-4cde-a7ec-9aa6b03f3e16 · outbound

This paper cites Scaling Laws for Neural Language Models.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Scaling Laws for Neural Language Models

Reference 4

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no resolver link, observed 2026-08-05T15:45:18.011418Z

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source=pdf_text observed=2026-08-05T15:45:18.011418Z digest=sha256:866162e80057b279abe71c0de847b061efd4e840a473aaf81181d3763ec45ec8

Observation ac2b975a-06ce-4f0f-adee-8a3e6cf2d42f · outbound

This paper cites BLIP: bootstrapping language-image pre-training for unified vision-language understanding and generation,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications BLIP: bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 5

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raw_fallback, observed 2026-08-05T15:45:20.040091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 0290cf59-d52a-4414-acfc-ce65772bd2d2 · outbound

This paper cites CoCa: Contrastive Captioners are Image-Text Foundation Models.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 6

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no resolver link, observed 2026-08-05T15:45:18.029223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:45:18.029223Z digest=sha256:f545ecb5fd28d0c53e975f98419ffe472e94ce65b931cfca2197dff718f7e36b

Observation bc8c858f-c802-4956-a6dc-58246f013fcc · outbound

This paper cites Large generative ai models for telecom: The next big thing?.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Large generative ai models for telecom: The next big thing?

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-05T15:45:19.904740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation dbe3927d-cde5-46fb-97f2-bf554861212d · outbound

This paper cites A fast multi-loss learning deep neural network for automatic modulation classification,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications A fast multi-loss learning deep neural network for automatic modulation classification,

Reference 8

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raw_fallback, observed 2026-08-05T15:45:19.827976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.040683Z digest=sha256:864356cc567601bcb23dedac7de81c1c3bf2915f32cc3e44272d57dc9d6e1176

Observation f84ac733-118a-4ad2-991a-599fb560c9a2 · outbound

This paper cites Joint signal detection and automatic modulation classification via deep learning,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Joint signal detection and automatic modulation classification via deep learning,

Reference 9

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raw_fallback, observed 2026-08-05T15:45:19.803105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.045721Z digest=sha256:16feb0eb39a8b84ad4f50cf652c63690d9837624fefa8c66bc2ba0ad60a2741f

Observation d19e87ff-cca3-493f-84e9-a157aedbcb79 · outbound

This paper cites Energy detection spectrum sensing under rf imperfections,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Energy detection spectrum sensing under rf imperfections,

Reference 10

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raw_fallback, observed 2026-08-05T15:45:19.741072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.050554Z digest=sha256:7e4525a6cae199883af28cd63a6466d008df6aa43d067ecb1e096885339d930c

Observation cdc0cf73-03a7-4785-a659-1db3c3cc9075 · outbound

This paper cites A cmos spectrum sensor based on quasi- cyclostationary feature detection for cognitive radios,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications A cmos spectrum sensor based on quasi- cyclostationary feature detection for cognitive radios,

Reference 11

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raw_fallback, observed 2026-08-05T15:45:19.713452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.055083Z digest=sha256:754c15fb1e0021c596cdc23643305caa6eff31a450cc9d37fe00d65a9f4d1fd0

Observation b2ab9e8a-9232-4081-9356-149667c6f565 · outbound

This paper cites Machine learning techniques for cooperative spectrum sensing in cognitive radio networks,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Machine learning techniques for cooperative spectrum sensing in cognitive radio networks,

Reference 12

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raw_fallback, observed 2026-08-05T15:45:19.647212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.059479Z digest=sha256:e4f754e05c5652f2c791601d98fd4d07ca3b62544b7ea657dde74d5998be1f0e

Observation 2c0d840b-b6ad-4514-b1e8-12dbb034d6ce · outbound

This paper cites Machine learning for spectrum sharing: A survey,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Machine learning for spectrum sharing: A survey,

Reference 13

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verified exact
doi, observed 2026-08-05T15:45:18.257463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.064039Z digest=sha256:d159606997c88af68c417dc5f172cf993ecab23d275299c8805f055259dbb45a

Observation 42e671f7-980a-456a-b057-99554af852ea · outbound

This paper cites Toolqa: A dataset for llm question answering with external tools,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Toolqa: A dataset for llm question answering with external tools,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-05T15:45:19.594088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.068857Z digest=sha256:fc37fcaeaa09fad2774df3d8758a68ea3c4a03bc6958f3cbc13d228500d2972d

Observation c20f982d-4565-4b0b-8f55-e2ea964c31c5 · outbound

This paper cites A survey on llm-generated text detection: Necessity, methods, and future directions,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications A survey on llm-generated text detection: Necessity, methods, and future directions,

Reference 15

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malformed identifier
no resolver link, observed 2026-08-05T15:45:18.073365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:45:18.073365Z digest=sha256:f9fda17fd70b50bba4ebfa5b874d2d867b06135ad54d494a346f5f0bfbda7ab2

Observation f069dfd9-30a7-4a27-8a87-b151b746d641 · outbound

This paper cites Wrist: Wideband, real-time, spectro-temporal rf identification system using deep learning,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Wrist: Wideband, real-time, spectro-temporal rf identification system using deep learning,

Reference 16

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raw_fallback, observed 2026-08-05T15:45:19.496813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.077817Z digest=sha256:d00ae7588517e8e9a03531b177f2b6b764023625c78bb17ba03db2606544b4e5

Observation 49a10a5f-fcb4-4e7f-95c9-47032888049e · outbound

This paper cites Deep Learning Object Detection Approaches to Signal Identification.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Deep Learning Object Detection Approaches to Signal Identification

Reference 17

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local_arxiv, observed 2026-08-05T15:45:18.465297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.082669Z digest=sha256:29a9c7986636a5fa8f0f5bae5a029bb8c1bf3122a89f391d3a06b1dc9e925e5a

Observation cef8da49-a970-402e-9cfc-c5bf2bd43c00 · outbound

This paper cites Sigmf: The signal metadata format,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Sigmf: The signal metadata format,

Reference 18

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raw_fallback, observed 2026-08-05T15:45:19.464739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.087714Z digest=sha256:69028efd4573113b6018bfe899f25f42a8ccef45e39a8cd402c51b1067334ec9

Observation d6a5a74d-8baf-4ed3-9dec-b7017ada6a47 · outbound

This paper cites Microsoft coco: Common objects in context,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Microsoft coco: Common objects in context,

Reference 19

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raw_fallback, observed 2026-08-05T15:45:19.375235Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.092522Z digest=sha256:e8c4ae4bf7eb4e68a7cb25604d0dc062d8f804219ff56075ede84109678ff9b1

Observation 135cfe1a-de04-4e85-8277-e4213b3d674b · outbound

This paper cites Top Choice: Get Your Certified Used N9040B UXA Signal Analyzer with Warranty - Keysight Technologies.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Top Choice: Get Your Certified Used N9040B UXA Signal Analyzer with Warranty - Keysight Technologies

Reference 20

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raw_fallback, observed 2026-08-05T15:45:19.336040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.097056Z digest=sha256:a5ef886e9e9101dbff808486e4541d0b4760ce4c9839238df3a4094c94dd6a4b

Observation 7f0d5fe0-fae4-46a3-af4f-9435b88ac952 · outbound

This paper cites Ettus Research - High performance Software Defined Radio (SDR).

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Ettus Research - High performance Software Defined Radio (SDR)

Reference 21

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raw_fallback, observed 2026-08-05T15:45:19.279818Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.101975Z digest=sha256:78f57faee05c21d5a79bc4326f98587c103e76ecac27df5ec2ada9350f7a6cd2

Observation 82f1f981-2635-43d4-b334-434b89604e98 · outbound

This paper cites Learning robust general radio signal detection using computer vision methods,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Learning robust general radio signal detection using computer vision methods,

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-05T15:45:19.236225Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.107077Z digest=sha256:115b11c7397e985932475f294699b8c2e2e4ee7b1fede068941cca88a0173bc6

Observation afee2527-e464-4a88-921d-119735abe323 · outbound

This paper cites A wideband signal recognition dataset,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications A wideband signal recognition dataset,

Reference 23

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raw_fallback, observed 2026-08-05T15:45:19.187794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.111454Z digest=sha256:52f2066ea446c11e334005b97070b052646fd9d67eec2d4d71ca46f55b409cae

Observation cc049613-fdc9-40d2-a1c9-2fd2c4e7fd8e · outbound

This paper cites Boost spectrum prediction with temporal-frequency fusion network via transfer learning,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Boost spectrum prediction with temporal-frequency fusion network via transfer learning,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-05T15:45:19.111560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.116092Z digest=sha256:b0356f77c099ffafd97adb4a636b1a65abbde9ecdaf8bdbe8536a16d7c167917

Observation 662055a2-2a3e-41ca-98f6-9b0ee6e09010 · outbound

This paper cites Joint detection and classification of rf signals using deep learning,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Joint detection and classification of rf signals using deep learning,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:45:18.994804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.120815Z digest=sha256:83c06e1ced5da4574804d4e1a31dd957198bf5797c55d8bbef2ed19cd4ec7128

Observation 6437e720-5340-4772-95d3-0b53fa1aba20 · outbound

This paper cites Vslm: Virtual signal large model for few-shot wideband signal detection and recognition,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Vslm: Virtual signal large model for few-shot wideband signal detection and recognition,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-05T15:45:18.937967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.126383Z digest=sha256:b41745ff38c3efcad49d0ad6796141077720b8a8e7d7764547f49a6ab0c446a4

Observation b2662787-b5e7-4d75-bf6b-de92513d9453 · outbound

This paper cites RadDet: A Wideband Dataset for Real-Time Radar Spectrum Detection.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications RadDet: A Wideband Dataset for Real-Time Radar Spectrum Detection

Reference 27

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verified exact
local_arxiv, observed 2026-08-05T15:45:18.442278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.130614Z digest=sha256:7bdcb4dceaf21b7c7de82d6f10e955e8b6ead8e0284090b2ef6b8e79085d2dfe

Observation 7c507d5b-678b-4506-b4d7-62c093e0fcaa · outbound

This paper cites Intelligent detection algorithm of broadband communication signal based on spectral decomposition,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Intelligent detection algorithm of broadband communication signal based on spectral decomposition,

Reference 28

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metadata mismatch
raw_fallback, observed 2026-08-05T15:45:18.419053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.135483Z digest=sha256:85427f2ea747764ad3d1016934ed5df3c2136d061d2c46b77a29c0d683b0af21

Observation 644854e3-5eb7-4b3a-865f-a94549cd4780 · outbound

This paper cites Colosseum: Large-scale wireless exper- imentation through hardware-in-the-loop network emulation,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Colosseum: Large-scale wireless exper- imentation through hardware-in-the-loop network emulation,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-05T15:45:18.846058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.140002Z digest=sha256:ca81406d16daea164dc824fcc40cd27c0fa69b00e07547cbdee2cef11623c599

Observation 5875807c-7a39-4082-bcb4-814fd1de5b9c · outbound

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

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Over-the-air deep learning based radio signal classification,

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-05T15:45:18.767095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.144987Z digest=sha256:c8218e2020a331d1d5b27dc43c21d4780cc2b64185051e739e68dba95805e15d

Observation f553cb86-d848-402a-ac9c-a436aaf9f6c0 · outbound

This paper cites An optimized faster region- based cnn for 1d spectrum sensing and signal identification in cluttered rf environments,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications An optimized faster region- based cnn for 1d spectrum sensing and signal identification in cluttered rf environments,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-05T15:45:18.708523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.149517Z digest=sha256:70169b7e4ed6df7055c43467e4f743c1a3c9841d554a9abae634c859e2945e03

Observation 3177f78e-ebc0-42f1-b5c7-08e6a94c5c54 · outbound

This paper cites Spectrogram data set for deep-learning-based rf frame detection,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Spectrogram data set for deep-learning-based rf frame detection,

Reference 32

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raw_fallback, observed 2026-08-05T15:45:18.657521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.154592Z digest=sha256:dd9fefcea46bfaba5d4ed032d9833635110c6088e399d2750faf24b31043bb0c

Observation dd998153-4e8f-47fa-95c5-236efc8625d9 · outbound

This paper cites Combined rf-based drone detection and classification,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Combined rf-based drone detection and classification,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:45:18.638958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.159581Z digest=sha256:10935730227c8fec9a37340d72fe760925806f46637943554103fc9b6048c8f6

Observation 188b931f-65db-476b-afd9-15ce28e282d3 · outbound

This paper cites A framework for wireless technology classification using crowdsensing platforms,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications A framework for wireless technology classification using crowdsensing platforms,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:45:18.620284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7dabb9c9-fabd-4a6d-b9e8-4711cf82652a · outbound

This paper cites Finding waldo in the cbrs band: Signal detection and localization in the 3.5 ghz spectrum,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Finding waldo in the cbrs band: Signal detection and localization in the 3.5 ghz spectrum,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:45:18.602610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation fbb8cf85-61e8-418a-a464-02d9534780db · outbound

This paper cites Large Scale Radio Frequency Wideband Signal Detection & Recognition.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Large Scale Radio Frequency Wideband Signal Detection & Recognition

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:45:18.285189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T15:45:18.174791Z digest=sha256:0a02fd958a142862808e6b8afcc4f25b88969bef960119a843bfc2e52336cc6d

Observation d90baaaf-dc50-411c-94fc-af3b63fc2b74 · outbound

This paper cites Hisarmod: A new challenging modulated signals dataset,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Hisarmod: A new challenging modulated signals dataset,

Reference 37

Resolution
verified exact
doi, observed 2026-08-05T15:45:18.227347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c1ded635-ac10-420e-8de2-cd816707a8e4 · outbound

This paper cites Rml22: Realistic dataset generation for wireless modulation classification,.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications Rml22: Realistic dataset generation for wireless modulation classification,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:45:18.579263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 10cbc99b-9abb-4ec1-92be-369fee70e022 · outbound

This paper cites 12 888–12 900.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications 12 888–12 900

Reference 162

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:45:19.951772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f428507f-08c9-4914-8365-57ca9c558ea7 · outbound

This paper cites DeepSeek-V3 Technical Report.

CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications DeepSeek-V3 Technical Report

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-05T15:45:17.999559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:45:17.999559Z digest=sha256:c30a6358bf1514e04cd770499845438adec3646fbd6ef94c9705ac9679fe1403

Pith citing papers

No inbound Pith citation observations are available.