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Paper Citation Record · LEDGER

A Reliable Framework for Human-in-the-Loop Anomaly Detection in Time Series

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.03234.

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

pith.paper-citation-record.v1
2405.03234 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:35:45.627694Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:36:50.544438Z

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 4a0360bf-57ba-4373-b482-c696f359e1e4 · inbound

Open Challenges in Time Series Anomaly Detection: An Industry Perspective cites this paper.

Open Challenges in Time Series Anomaly Detection: An Industry Perspective A Reliable Framework for Human-in-the-Loop Anomaly Detection in Time Series

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-08T19:35:45.627694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:35:45.627694Z digest=sha256:726455bd5efe3d2ceb5b7ca8f1f6011b9834a9dcd6ace7312779c46eff1f62de

Observation 36ef914b-a060-49d1-a8ec-59918348b329 · inbound

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation cites this paper.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation A Reliable Framework for Human-in-the-Loop Anomaly Detection in Time Series

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:36:50.628452Z

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=2026-08-06T22:36:42.807218Z digest=sha256:922ffe50aec747633b8055c68f7cbc889f1db2b284a5985ee7c4e512e69096da