Paper Citation Record · LEDGER

Self-supervised learning for radio-astronomy source classification: a benchmark

As of 13 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2411.14078.

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

pith.paper-citation-record.v1
2411.14078 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:39:08.863122Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T00:17:58.936783Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

35 of 35 outbound references displayed

verified exact0
verified fuzzy17
unresolved16
parse uncertain0
malformed identifier1
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External citation measurements

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 5747c032-622b-45b0-bf73-a7abb541e07e · outbound

This paper cites The Hidden Uniform Cluster Prior in Self-Supervised Learning.

Self-supervised learning for radio-astronomy source classification: a benchmark The Hidden Uniform Cluster Prior in Self-Supervised Learning

Reference 1

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Source-reported events for the cited work

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Observation 85422ec9-fdce-43c9-83b6-fb3076b05dba · outbound

This paper cites Monthly Notices of the Royal Astronomical Society453(3), 2326–2340 (2015).

Self-supervised learning for radio-astronomy source classification: a benchmark Monthly Notices of the Royal Astronomical Society453(3), 2326–2340 (2015)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.419609Z

Source-reported events for the cited work

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Observation 3514f9ba-9329-4ef8-87aa-f809861f6d2b · outbound

This paper cites Astrophysical Journal v.

Self-supervised learning for radio-astronomy source classification: a benchmark Astrophysical Journal v

Reference 3

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Observation 560c2606-2634-4ebd-937b-60bbeeebb34d · outbound

This paper cites In: ML4Astro International Conference.

Self-supervised learning for radio-astronomy source classification: a benchmark In: ML4Astro International Conference

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.394323Z

Source-reported events for the cited work

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Observation 430dc6b7-314f-41ac-8468-464a1d07a047 · outbound

This paper cites Advances in neural information processing systems33, 9912–9924 (2020).

Self-supervised learning for radio-astronomy source classification: a benchmark Advances in neural information processing systems33, 9912–9924 (2020)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:08.737948Z

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Observation e68cf520-0a20-457c-9860-610e4b2583ea · outbound

This paper cites In: Proceedings of the International Conference on Computer Vision (ICCV) (2021).

Self-supervised learning for radio-astronomy source classification: a benchmark In: Proceedings of the International Conference on Computer Vision (ICCV) (2021)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:08.742756Z

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Observation 2008fd73-011e-40a3-bfa3-166abfbc38a5 · outbound

This paper cites In: International conference on machine learning.

Self-supervised learning for radio-astronomy source classification: a benchmark In: International conference on machine learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:08.747488Z

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Observation 01ac2f35-17fd-42d7-86cd-44d36ab25363 · outbound

This paper cites Evaluating Deep Learning in SystemML using Layer-wise Adaptive Rate Scaling(LARS) Optimizer.

Self-supervised learning for radio-astronomy source classification: a benchmark Evaluating Deep Learning in SystemML using Layer-wise Adaptive Rate Scaling(LARS) Optimizer

Reference 8

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Observation 6a1fc604-6e4f-4378-bddd-99eb3afd53ab · outbound

This paper cites an unresolved cited work.

Self-supervised learning for radio-astronomy source classification: a benchmark Unresolved cited work

Reference 9

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Source-reported events for the cited work

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Observation 1219b996-cbd1-49f9-a0c0-d439d70e77cc · outbound

This paper cites SKA Organisation, Design Report SKA-TEL-SKO-0000002, Rev3 (2016).

Self-supervised learning for radio-astronomy source classification: a benchmark SKA Organisation, Design Report SKA-TEL-SKO-0000002, Rev3 (2016)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.344742Z

Source-reported events for the cited work

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Observation b4fb7e60-8289-4d18-b858-95b2a4d9ad04 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Self-supervised learning for radio-astronomy source classification: a benchmark An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:08.764100Z

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Observation 0166f258-7941-430f-a194-a7d039e5e3a6 · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

Self-supervised learning for radio-astronomy source classification: a benchmark In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 12

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Source-reported events for the cited work

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Observation 7317d7f8-5a22-43d3-b968-4f17625a2daa · outbound

This paper cites In: International Conference on Machine Learning.

Self-supervised learning for radio-astronomy source classification: a benchmark In: International Conference on Machine Learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.319144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e6954398-293e-4959-82c1-dcb902abe3f0 · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision (2023).

Self-supervised learning for radio-astronomy source classification: a benchmark In: Proceedings of the IEEE/CVF International Conference on Computer Vision (2023)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.307247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9fb40137-a6c8-4ec8-b79b-1be1f1696de7 · outbound

This paper cites The SARAO MeerKAT 1.3 GHz Galactic Plane Survey.

Self-supervised learning for radio-astronomy source classification: a benchmark The SARAO MeerKAT 1.3 GHz Galactic Plane Survey

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:08.781577Z

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Observation 1327f238-1b26-4c3b-b812-44e85124ed3e · outbound

This paper cites Monthly Notices of the Royal Astronomical Society531(1), 649–681 (2024).

Self-supervised learning for radio-astronomy source classification: a benchmark Monthly Notices of the Royal Astronomical Society531(1), 649–681 (2024)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.294786Z

Source-reported events for the cited work

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Observation fa3fefba-c3f3-4b58-b47f-cc12b878ff12 · outbound

This paper cites an unresolved cited work.

Self-supervised learning for radio-astronomy source classification: a benchmark Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:39:09.278399Z

Source-reported events for the cited work

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Observation 5b455b5b-d412-46eb-a1a5-ba2a650023bd · outbound

This paper cites Advances in neural information processing systems 33, 21271–21284 (2020).

Self-supervised learning for radio-astronomy source classification: a benchmark Advances in neural information processing systems 33, 21271–21284 (2020)

Reference 18

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Source-reported events for the cited work

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Observation c2feed1e-401b-4df7-8652-e194ff043507 · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

Self-supervised learning for radio-astronomy source classification: a benchmark In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 19

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Source-reported events for the cited work

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Observation f63533ad-827e-4f1a-ab4b-d3fd707e6dc8 · outbound

This paper cites RAS Techniques and Instruments2(1), 441–452 (2023).

Self-supervised learning for radio-astronomy source classification: a benchmark RAS Techniques and Instruments2(1), 441–452 (2023)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.249314Z

Source-reported events for the cited work

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Observation 87c7ba66-33df-4e23-a28d-9eeecc8ad187 · outbound

This paper cites IEEE Transactions on Knowledge and Data Engineering 35(1), 857–876 (2023).

Self-supervised learning for radio-astronomy source classification: a benchmark IEEE Transactions on Knowledge and Data Engineering 35(1), 857–876 (2023)

Reference 21

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Source-reported events for the cited work

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Observation 8ebf4700-db5d-41d3-9b45-d6767aa8ad9a · outbound

This paper cites Astronomy and Computing 36, 100481 (2021).

Self-supervised learning for radio-astronomy source classification: a benchmark Astronomy and Computing 36, 100481 (2021)

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:08.808761Z

Source-reported events for the cited work

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Observation db0fbc5d-8dbe-4c27-aa5b-5faeb43e9e0f · outbound

This paper cites Decoupled Weight Decay Regularization.

Self-supervised learning for radio-astronomy source classification: a benchmark Decoupled Weight Decay Regularization

Reference 23

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Source-reported events for the cited work

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Observation 015fbe78-d2db-46b5-90ee-7ce16e9c584b · outbound

This paper cites Monthly Notices of the Royal Astronomi- cal Society 530(1), 1274–1295 (2024).

Self-supervised learning for radio-astronomy source classification: a benchmark Monthly Notices of the Royal Astronomi- cal Society 530(1), 1274–1295 (2024)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.236032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 46656726-035a-419f-bc6d-83cae66b549e · outbound

This paper cites Astronomy & Astrophysics645, A89 (2021).

Self-supervised learning for radio-astronomy source classification: a benchmark Astronomy & Astrophysics645, A89 (2021)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.224036Z

Source-reported events for the cited work

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Observation d95c1dbf-c85d-4cb0-90c4-fc0d74cfcacf · outbound

This paper cites Publications of the Astronomical Society of Australia28(3), 215–248 (2011).

Self-supervised learning for radio-astronomy source classification: a benchmark Publications of the Astronomical Society of Australia28(3), 215–248 (2011)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.210723Z

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Observation 29a6b4ca-1b3e-481b-8fb9-f80d3e5ca812 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Self-supervised learning for radio-astronomy source classification: a benchmark DINOv2: Learning Robust Visual Features without Supervision

Reference 27

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Observation 4241bc17-721f-4675-879c-a7f9a02a5905 · outbound

This paper cites RAS Techniques and Instruments2(1), 293– 306 (06 2023).https://doi.org/10.1093/rasti/rzad017 16 Cecconello et al.

Self-supervised learning for radio-astronomy source classification: a benchmark RAS Techniques and Instruments2(1), 293– 306 (06 2023).https://doi.org/10.1093/rasti/rzad017 16 Cecconello et al

Reference 28

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Observation aa6122d8-d8fe-4e5f-b9f5-859b7f84c05e · outbound

This paper cites Self-supervised contrastive learning of radio data for source detection, classification and peculiar object discovery.

Self-supervised learning for radio-astronomy source classification: a benchmark Self-supervised contrastive learning of radio data for source detection, classification and peculiar object discovery

Reference 29

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Source-reported events for the cited work

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Observation 5381085d-b571-4078-97e0-be7e7ddb9529 · outbound

This paper cites Astronomy and Computing 42, 100682 (2023).

Self-supervised learning for radio-astronomy source classification: a benchmark Astronomy and Computing 42, 100682 (2023)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.194691Z

Source-reported events for the cited work

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Observation 7eb74d16-d656-4aa2-b1a1-3b51c1a54366 · outbound

This paper cites Publications of the Astronomical Society of Australia41, e029 (2024).

Self-supervised learning for radio-astronomy source classification: a benchmark Publications of the Astronomical Society of Australia41, e029 (2024)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.182286Z

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Observation df723057-5825-4e1e-91e8-b6bbbe9f3f7f · outbound

This paper cites The Astrophysical Journal921(2), 177 (2021).

Self-supervised learning for radio-astronomy source classification: a benchmark The Astrophysical Journal921(2), 177 (2021)

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.167762Z

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Observation 96e2c394-009b-4429-b01c-662bc5ac113e · outbound

This paper cites RAS Techniques and Instruments 3(1), 19–32 (12 2023).

Self-supervised learning for radio-astronomy source classification: a benchmark RAS Techniques and Instruments 3(1), 19–32 (12 2023)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.154104Z

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Observation 1e8c5738-23fb-455a-bd8a-b9b43c1db2a6 · outbound

This paper cites Monthly Notices of the Royal Astronomical Society 454(1), 902–912 (2015).

Self-supervised learning for radio-astronomy source classification: a benchmark Monthly Notices of the Royal Astronomical Society 454(1), 902–912 (2015)

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:09.141692Z

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Observation 289908d5-780b-46b6-806b-99cac352c4ef · outbound

This paper cites In: International Conference on Machine Learn- ing.

Self-supervised learning for radio-astronomy source classification: a benchmark In: International Conference on Machine Learn- ing

Reference 35

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Pith citing papers

Observation fe04b073-368c-420d-b245-044a5fd01e00 · inbound

Source Finding and Characterisation for SKAO Science cites this paper.

Source Finding and Characterisation for SKAO Science Self-supervised learning for radio-astronomy source classification: a benchmark

Reference 83

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Source-reported events for the cited work

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