Paper Citation Record · LEDGER

Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2412.03454.

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

pith.paper-citation-record.v1
2412.03454 v3

Coverage vector

measured 0 of 0 reference resolution

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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 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:39:16.349154Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T00:36:24.982108Z

Reference resolution

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ad3c1181-7d15-4ca1-a319-044eab58fbfc · inbound

Hierarchical Subtraction with Neural Density Estimators as a General Solution to Overlapping Gravitational Wave Signals cites this paper.

Hierarchical Subtraction with Neural Density Estimators as a General Solution to Overlapping Gravitational Wave Signals Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T19:39:16.349154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e05e19d-993e-4080-93ca-56398bf31ec8 · inbound

Fast neural network surrogate for multimodal effective-one-body gravitational waveforms from generically precessing compact binaries cites this paper.

Fast neural network surrogate for multimodal effective-one-body gravitational waveforms from generically precessing compact binaries Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:46:32.408639Z

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.

Observation 836c2bfc-598f-4945-b5a0-de2a115fcaf8 · inbound

Speed and accuracy for long signals: Frequency-domain effective-one-body waveforms for compact binary coalescences cites this paper.

Speed and accuracy for long signals: Frequency-domain effective-one-body waveforms for compact binary coalescences Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-07-02T00:36:24.985307Z

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.

Observation 654d6b95-9950-4949-828e-2905baf6aaee · inbound

nmma: An extended Bayesian framework for Nuclear Multimessenger Astronomy in the Era of Next-Generation Detectors cites this paper.

nmma: An extended Bayesian framework for Nuclear Multimessenger Astronomy in the Era of Next-Generation Detectors Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State

Reference 95

Resolution: unresolved; no resolver link, observed 2026-07-12T05:14:58.841553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58a64cff-82d0-48ce-a604-033dd5430f3a · inbound

Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms cites this paper.

Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State

Reference 55

Resolution: unresolved; no resolver link, observed 2026-07-31T04:58:16.815444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9be71712-04c6-4dad-9d3f-3388d7719404 · inbound

Ab Initio Real-Time Gravitational-Wave Parameter Estimation cites this paper.

Ab Initio Real-Time Gravitational-Wave Parameter Estimation Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State

Reference 79

Resolution: unresolved; no resolver link, observed 2026-07-31T12:51:48.884508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.