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Paper Citation Record · LEDGER

Applications of machine learning in gravitational wave research with current interferometric detectors

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2412.15046.

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

pith.paper-citation-record.v1
2412.15046 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:29:56.883255Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 052d7d6a-5ba4-4330-ad77-d28a7e783bab · inbound

Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation cites this paper.

Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation Applications of machine learning in gravitational wave research with current interferometric detectors

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T18:29:56.883255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:29:56.883255Z digest=sha256:ed187847676cac9e268c78d04dd6f047226d348b70efab65a7880fc8bf65017b

Observation cf11e007-c9ae-45cd-adab-6849e230d57e · inbound

The Early Career Workshop of GR-Amaldi 2025 cites this paper.

The Early Career Workshop of GR-Amaldi 2025 Applications of machine learning in gravitational wave research with current interferometric detectors

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:26:47.975840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T19:25:07.438670Z digest=sha256:e1409851af1b3473086b5a40dbbd29cc2dceca678c67148c09ae5ca05d74e9d2

Observation 56c09d88-a52d-4f5c-8a54-bc5efa0eccbe · inbound

Auto-encoder model for faster generation of effective one-body gravitational waveform approximations cites this paper.

Auto-encoder model for faster generation of effective one-body gravitational waveform approximations Applications of machine learning in gravitational wave research with current interferometric detectors

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:10:21.760611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T22:06:32.129237Z digest=sha256:9b7bbf395df1223561698406ab0532f53d7c1bea669a561ef605f69e4b867666

Observation 7ee91d00-9589-488c-b153-fd16d82f3e7d · inbound

VIGILant: an automatic classification pipeline for glitches in the Virgo detector cites this paper.

VIGILant: an automatic classification pipeline for glitches in the Virgo detector Applications of machine learning in gravitational wave research with current interferometric detectors

Reference 23

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verified exact
arxiv_id, observed 2026-05-11T11:41:06.288289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T12:41:50.796918Z digest=sha256:0261ba4395518ec9d85cd6f911b2b57ab8100c297a3aa6d79c9ad9876d8657d2

Observation 82a29501-98d9-4bcf-b95e-74bb3b48c017 · inbound

Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection cites this paper.

Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection Applications of machine learning in gravitational wave research with current interferometric detectors

Reference 137

Resolution
verified exact
arxiv_id, observed 2026-05-21T03:33:56.412517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T03:33:53.198336Z digest=sha256:e473441f46e3605b25959e0c28a664eb1d4d847de4a5bcda2a70e85bb0f1dc0b

Observation f06f3cee-741c-471d-8da8-3252f0e8fcfc · inbound

Massive boson stars: Waveform-based branch diagnosis with neural reconstruction cites this paper.

Massive boson stars: Waveform-based branch diagnosis with neural reconstruction Applications of machine learning in gravitational wave research with current interferometric detectors

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:09:56.285294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T01:03:12.416132Z digest=sha256:bdd0f45aebe0c455faf8236cedc2f47f171de89f541b8f4bcc36aa7dd7abb2be

Observation 80e10a63-b744-424f-8ec0-83c869d52865 · inbound

GW Microlensing: Degeneracy with Unlensed Precessing and Non-Spinning Gravitational-Wave Signals cites this paper.

GW Microlensing: Degeneracy with Unlensed Precessing and Non-Spinning Gravitational-Wave Signals Applications of machine learning in gravitational wave research with current interferometric detectors

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-01T22:01:50.847371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:01:50.847371Z digest=sha256:241fc8790614b03bb47cda273f20c1915d8f88d224af4d96c312f4bf4df66625

Observation 3436959d-af95-4563-b75f-29672bd27a52 · inbound

Addressing rotational motion on gravitational waves detectors cites this paper.

Addressing rotational motion on gravitational waves detectors Applications of machine learning in gravitational wave research with current interferometric detectors

Reference 124

Resolution
unresolved
no resolver link, observed 2026-08-01T16:09:46.340240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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