Paper Citation Record · LEDGER

Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data

As of 19 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 2 inbound Pith citation observations for arXiv:2411.19450.

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

pith.paper-citation-record.v1
2411.19450 v2

Coverage vector

measured 8 of 8 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:14:05.280143Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:15:48.002304Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T12:15:48.477454Z

Reference resolution

8 of 8 outbound references displayed

verified exact1
verified fuzzy3
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c5ca13d6-b466-4aa5-a74c-c03c54a7c495 · outbound

This paper cites Zhou and R.

Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data Zhou and R

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:14:05.359925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6cce8539-c950-41d8-a004-4733635df028 · outbound

This paper cites Hierarchical Strategies for Cooperative Multi-Agent Reinforcement Learning.

Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data Hierarchical Strategies for Cooperative Multi-Agent Reinforcement Learning

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-12T10:14:05.320259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8ebf38a5-e2f8-4b25-bc05-71b442c0eea5 · outbound

This paper cites Finke, M.

Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data Finke, M

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:14:05.351186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5fcd7fd4-cc9a-40dd-9461-d44dbd20f3e4 · outbound

This paper cites an unresolved cited work.

Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-12T10:14:05.342522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 512e22fc-6eda-4d72-b5a4-ac9097c4cd6a · outbound

This paper cites Auto-Encoding Variational Bayes.

Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data Auto-Encoding Variational Bayes

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T10:14:05.271273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5da74c28-582a-4c30-9522-f900ec84798f · outbound

This paper cites Cuoco, G.

Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data Cuoco, G

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:14:05.334051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4d5bc646-11fe-459a-a86e-aadacf5607d3 · outbound

This paper cites Hochreiter, Neural Computation MIT-Press (1997).

Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data Hochreiter, Neural Computation MIT-Press (1997)

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T10:14:05.277498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a6e91ad-86ee-40bc-b206-c21c5cfabb20 · outbound

This paper cites GWAK: Gravitational-Wave Anomalous Knowledge with Recurrent Autoencoders.

Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data GWAK: Gravitational-Wave Anomalous Knowledge with Recurrent Autoencoders

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T10:14:05.280143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9d9a74c0-8489-456a-96bd-d3659e8254cd · inbound

Template-Free Gravitational Wave Detection with CWT-LSTM Autoencoders: A Case Study of Run-Dependent Calibration Effects in LIGO Data cites this paper.

Template-Free Gravitational Wave Detection with CWT-LSTM Autoencoders: A Case Study of Run-Dependent Calibration Effects in LIGO Data Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-05T12:15:48.533335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation beba75fa-e590-485e-adc4-eea4c5b2fdef · inbound

Global Structure in Learned Latent Representations of Confusion-Limited LISA Data cites this paper.

Global Structure in Learned Latent Representations of Confusion-Limited LISA Data Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T21:38:37.894911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.