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Paper Citation Record · LEDGER

Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.19003.

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

pith.paper-citation-record.v1
2305.19003 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:30:31.333922Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T03:33:56.341829Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 5e7dc6e5-2aa4-4686-818e-d03e80bb01e7 · inbound

Parameter inference of millilensed gravitational waves using neural spline flows cites this paper.

Parameter inference of millilensed gravitational waves using neural spline flows Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-05-19T13:22:18.532394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T13:21:37.451964Z digest=sha256:bb5efc3a6ca4270f83a030a2693902c26975f9116a28feffaa2d531e2acea74f

Observation 780f36db-7cd1-4414-b4e5-e2f3f4233dfc · inbound

Robustness of Sensitivity Evaluations for Gravitational Wave Detection Algorithms cites this paper.

Robustness of Sensitivity Evaluations for Gravitational Wave Detection Algorithms Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-05T05:30:31.333922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:30:31.333922Z digest=sha256:f9703259a19eba5502b6dd7839ac242c03e1732efa6eca5e0f3d0ebd682cb0a4

Observation 9d5b87bb-4a61-47f3-b515-db3b79b856ea · inbound

Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows cites this paper.

Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning

Reference 90

Resolution
verified exact
arxiv_id, observed 2026-05-10T12:50:25.805463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T12:44:04.023275Z digest=sha256:f0eebcab97196472b81f0d133267f3315c162e77b0553d3c403edfc9aed4209f

Observation 0b63ef22-2e61-4315-bf54-d6c90919f804 · 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 Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning

Reference 131

Resolution
verified exact
arxiv_id, observed 2026-05-21T03:33:56.343428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T03:33:53.198336Z digest=sha256:3e0ac28922fad802f93f642aeba7868ec347c7599a096f7c714c6a938b7ae687

Observation 4a24a909-6bc3-4102-820c-c08c507ce897 · inbound

Identifying lensed gravitational waves with physics-informed posterior learning cites this paper.

Identifying lensed gravitational waves with physics-informed posterior learning Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning

Reference 130

Resolution
unresolved
no resolver link, observed 2026-07-11T23:16:00.672720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T23:16:00.672720Z digest=sha256:a9934f22d276545f646c164e642078a2fd92307e27e1419dcc80efdf170784ad