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Paper Citation Record · LEDGER

Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2401.15123.

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

pith.paper-citation-record.v1
2401.15123 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:57:35.458156Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T09:32:15.883434Z

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 4669bf09-bdff-49ad-a831-3252b047ab39 · inbound

KKA: Improving Vision Anomaly Detection through Anomaly-related Knowledge from Large Language Models cites this paper.

KKA: Improving Vision Anomaly Detection through Anomaly-related Knowledge from Large Language Models Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T19:57:35.458156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:57:35.458156Z digest=sha256:d23d55038fda5358cd212d9db2aa029204c631827015a4b95a9fe06ed9c50288

Observation 393bc5ac-613b-447a-939c-44e21c4f37c4 · inbound

Large Language models for Time Series Analysis: Techniques, Applications, and Challenges cites this paper.

Large Language models for Time Series Analysis: Techniques, Applications, and Challenges Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection

Reference 104

Resolution
unresolved
no resolver link, observed 2026-08-07T15:26:59.331980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:26:59.331980Z digest=sha256:afbc4ebf0420061673932d19bbcb7d469d3ee67047182f7049aef34ac8ecfdf1

Observation 71f743d5-7551-4ec7-847c-9c0eb43cb3bd · 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 Model Guided Knowledge Distillation for Time Series Anomaly Detection

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-19T09:32:15.886621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-19T09:31:55.829045Z digest=sha256:15c8da7e720a281fc689058e6cca54520366cc8ee76c1a0ea4f515ff0a1aed58

Observation 2fa1d73e-790e-4c97-a45a-b179cb9d5454 · 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 Model Guided Knowledge Distillation for Time Series Anomaly Detection

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-19T03:32:01.436435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-19T03:30:00.958369Z digest=sha256:91ff9e1c45249bdeb9030cfac4d82520c33f0afd67339e2943064fee2c1a1f3b