Paper Citation Record · LEDGER

Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2405.15370.

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

pith.paper-citation-record.v1
2405.15370 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:29:56.760528Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:26:22.002851Z

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 67f733c6-f299-43fb-ac90-d86040203bd5 · inbound

Large Language Model-Brained GUI Agents: A Survey cites this paper.

Large Language Model-Brained GUI Agents: A Survey Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-05-19T11:08:27.649616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4ce75447-a7e3-4b14-8094-3317e4a2a0ef · inbound

Large Action Models: From Inception to Implementation cites this paper.

Large Action Models: From Inception to Implementation Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T16:29:56.760528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9953e368-fb0c-4a4b-ba5d-3ff2b53da1c1 · inbound

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models cites this paper.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.244235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9c50eb7-9e3a-4fa5-b198-e0a1c783d556 · inbound

Foundation Models for Anomaly Detection: Vision and Challenges cites this paper.

Foundation Models for Anomaly Detection: Vision and Challenges Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T16:34:14.328630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 976b4d39-eb63-42f7-bc7a-58760128375e · inbound

From Time Series Analysis to Question Answering: A Survey in the LLM Era cites this paper.

From Time Series Analysis to Question Answering: A Survey in the LLM Era Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:32:15.917827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 59b9d7c2-e72b-408c-972b-ffa83cebb413 · inbound

Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback cites this paper.

Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:32:01.422165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ff5bcd3c-c705-4b15-93b2-860c8b863188 · inbound

IstGPT: LLM-based Anomaly Detection for Spatial-Temporal Graph in Industrial Systems cites this paper.

IstGPT: LLM-based Anomaly Detection for Spatial-Temporal Graph in Industrial Systems Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:26:22.004957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0a230d75-64f3-4308-934f-a50a1c1456a3 · inbound

C-RE-ACT: Causal RE-ACTing Agent for O-RAN Forensic Triage cites this paper.

C-RE-ACT: Causal RE-ACTing Agent for O-RAN Forensic Triage Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:40.189581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.