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Paper Citation Record · LEDGER

Can LLMs Serve As Time Series Anomaly Detectors?

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2408.03475.

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

pith.paper-citation-record.v1
2408.03475 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:46:35.222766Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T00:08:21.806717Z

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 d08324d2-61a8-4444-b211-ba5265bce635 · inbound

An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework cites this paper.

An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework Can LLMs Serve As Time Series Anomaly Detectors?

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T23:04:09.407252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:04:09.407252Z digest=sha256:1f6eebcaee17dd8db83ccf79e0c10b7eca0835c12c597d00640aa51f4f27c710

Observation 75ae5ac0-d944-4221-a3be-ec74c9056458 · inbound

Multi-Agent Collaboration Mechanisms: A Survey of LLMs cites this paper.

Multi-Agent Collaboration Mechanisms: A Survey of LLMs Can LLMs Serve As Time Series Anomaly Detectors?

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-13T15:54:54.462659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-13T15:54:54.146003Z digest=sha256:0c6e19190dca93bce6a1fb6b010acc127bcbfc4750a3acae2dbb3bb7a8b16646

Observation 36830a1c-bdbf-4fff-9f76-7f5a3318b7f6 · inbound

Toxicity Begets Toxicity: Unraveling Conversational Chains in Political Podcasts cites this paper.

Toxicity Begets Toxicity: Unraveling Conversational Chains in Political Podcasts Can LLMs Serve As Time Series Anomaly Detectors?

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T17:02:51.039884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:02:51.039884Z digest=sha256:83e6cd3be4ba3e314b27fb353c95fd33f0cb1393fb6fedca52fe077a1bad310e

Observation fd68b646-fee8-43ee-9f85-b28b3da4b266 · 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 Can LLMs Serve As Time Series Anomaly Detectors?

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T15:25:07.146038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:07.146038Z digest=sha256:90ceb7089d66f0d8061671d4732b758aa01fd5cadb8266684872f1c02449a930

Observation b067b791-ffcf-41a1-9bd4-d7d28d8a957d · inbound

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

Foundation Models for Anomaly Detection: Vision and Challenges Can LLMs Serve As Time Series Anomaly Detectors?

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-08T16:34:14.280535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:34:14.280535Z digest=sha256:40e063c7d7a62a30438ba9de7f54b218d7eb61e884ed6e5ff6473618d948ccd0

Observation 35730704-330e-49f5-8443-3f255e8b6c64 · inbound

Towards Time Series Generation Conditioned on Unstructured Natural Language cites this paper.

Towards Time Series Generation Conditioned on Unstructured Natural Language Can LLMs Serve As Time Series Anomaly Detectors?

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T21:59:18.056078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:59:18.056078Z digest=sha256:0e25548583393b7a72360be1570f06a2e0d97c46735ab55294149930057851f6

Observation f70c1cff-4e9d-4726-a6c3-49081102c407 · inbound

Text-ADBench: Text Anomaly Detection Benchmark based on LLMs Embedding cites this paper.

Text-ADBench: Text Anomaly Detection Benchmark based on LLMs Embedding Can LLMs Serve As Time Series Anomaly Detectors?

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-06T16:57:24.085163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:57:24.085163Z digest=sha256:acb16b9cbf451640a9234f501974bb42b2840ba80d2a37a0f93ec6502859d8d0

Observation f86e91a3-5a37-4ae5-94d6-8d2902c3ea70 · inbound

Human-AI Collaborative Bot Detection in MMORPGs cites this paper.

Human-AI Collaborative Bot Detection in MMORPGs Can LLMs Serve As Time Series Anomaly Detectors?

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T16:46:35.222766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:46:35.222766Z digest=sha256:926aaffa32b312ff19b975e5e17b6817eb1ff4913ac5f98b34d7e57e22b2bb9a

Observation 7f2fdb6d-cf71-4fa6-b8bb-be02c00dc4ab · inbound

BALM-TSF: Balanced Multimodal Alignment for LLM-Based Time Series Forecasting cites this paper.

BALM-TSF: Balanced Multimodal Alignment for LLM-Based Time Series Forecasting Can LLMs Serve As Time Series Anomaly Detectors?

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T13:29:01.156871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:29:01.156871Z digest=sha256:d20d5934b733299d579bce5274b39720e4a569c875234242ab33c669d20c3a5f

Observation 2fb4d806-6083-4126-bae0-bede3d71d078 · inbound

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models cites this paper.

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models Can LLMs Serve As Time Series Anomaly Detectors?

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-04T16:49:27.831633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T16:49:27.831633Z digest=sha256:6372bb867399c2ac974b9823464ca27474abccf8774cc01494a6129b2ece90c3

Observation 553a2c13-9ba0-49dc-ad7f-71629e23096f · inbound

AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning cites this paper.

AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning Can LLMs Serve As Time Series Anomaly Detectors?

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-02T23:29:45.967507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:29:45.967507Z digest=sha256:7726e4e5297af7e32da036dd396706e85a3a9443277d809e9ab0f508cc6ac3e4

Observation 4ff906f2-a92e-4a3b-a5cc-98163870b092 · inbound

VAN-AD: Visual Masked Autoencoder with Normalizing Flow For Time Series Anomaly Detection cites this paper.

VAN-AD: Visual Masked Autoencoder with Normalizing Flow For Time Series Anomaly Detection Can LLMs Serve As Time Series Anomaly Detectors?

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-15T00:08:21.808250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T00:04:05.071623Z digest=sha256:4b579864057260704b0662a119fdad42c3658e0755661e0b26944e6e029a37e9

Observation c6cb2ec8-f26f-4ddb-b1d5-fdf1d8ae607b · inbound

VAN-AD: Visual Masked Autoencoder with Normalizing Flow For Time Series Anomaly Detection cites this paper.

VAN-AD: Visual Masked Autoencoder with Normalizing Flow For Time Series Anomaly Detection Can LLMs Serve As Time Series Anomaly Detectors?

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-02T17:22:59.771104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T17:22:59.771104Z digest=sha256:e4409a1fcb2038e892d84b12822164671525df147dc98b1779fb4b6f280fa6fe