Paper Citation Record · LEDGER

New Gravitational Wave Discoveries Enabled by Machine Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2407.07820.

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

pith.paper-citation-record.v1
2407.07820 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:29:53.965204Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T19:46:14.820881Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 11cf93ac-c44b-4251-ba69-bb3b70ac1b65 · 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 New Gravitational Wave Discoveries Enabled by Machine Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:53.965204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be02d2da-8aab-4151-a7e2-c009398e34a4 · inbound

Flexible Gravitational-Wave Parameter Estimation with Transformers cites this paper.

Flexible Gravitational-Wave Parameter Estimation with Transformers New Gravitational Wave Discoveries Enabled by Machine Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T18:59:09.787827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c6de2b7-8056-4d51-87d5-0778c5e4d3eb · inbound

Searching for binary black hole mergers with deep learning in Advanced LIGO's third observing run cites this paper.

Searching for binary black hole mergers with deep learning in Advanced LIGO's third observing run New Gravitational Wave Discoveries Enabled by Machine Learning

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T18:39:17.125400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc0d3332-9d57-48a0-9077-78a64d9631e8 · inbound

Beyond Gaussian Assumptions: A new robust statistical framework for gravitational-wave data analysis cites this paper.

Beyond Gaussian Assumptions: A new robust statistical framework for gravitational-wave data analysis New Gravitational Wave Discoveries Enabled by Machine Learning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-02T20:55:47.844518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43617c77-05e1-4632-bfa3-4b5725101882 · inbound

GW190711_030756 and GW200114_020818: astrophysical interpretation of two asymmetric binary black hole mergers in the IAS catalog cites this paper.

GW190711_030756 and GW200114_020818: astrophysical interpretation of two asymmetric binary black hole mergers in the IAS catalog New Gravitational Wave Discoveries Enabled by Machine Learning

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T00:35:51.516903Z

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.

Observation 4f4ae153-7c0a-4ffe-90e8-58b3d4b1213d · inbound

Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective cites this paper.

Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective New Gravitational Wave Discoveries Enabled by Machine Learning

Reference 280

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:46:14.823957Z

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.