Paper Citation Record · LEDGER

Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2409.01980.

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

pith.paper-citation-record.v1
2409.01980 v3

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 2026-08-17T06:30:58.91139+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:59:45.488563Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a0e2aebe-a763-463b-abe3-4f2ae37f8ed8 · inbound

A Comprehensive Survey on Integrating Large Language Models with Knowledge-Based Methods cites this paper.

A Comprehensive Survey on Integrating Large Language Models with Knowledge-Based Methods Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-10T18:34:59.744274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4232b27c-c293-40b9-be09-6c27fa52ebcf · inbound

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

Foundation Models for Anomaly Detection: Vision and Challenges Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T16:34:14.379095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8824dfc3-a391-44da-b92e-0cc713a8bc38 · inbound

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs cites this paper.

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-22T09:41:22.232271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 767e96e0-c0c7-4d4f-8938-3e442a7e95b6 · inbound

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs cites this paper.

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-05-22T09:41:21.344656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3e377bf9-335e-43c3-a57e-8f6028e00f3e · inbound

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs cites this paper.

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-06-30T17:34:58.049292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 63b633a9-2f8f-49b7-9dcc-5f31462fc7b5 · inbound

Node-to-Neighborhood Semantic Consistency: Text-Topology Alignment for TAGs Anomaly Detection cites this paper.

Node-to-Neighborhood Semantic Consistency: Text-Topology Alignment for TAGs Anomaly Detection Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T06:54:21.424918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation aee530a5-9b84-4072-8961-0f42f47b2666 · inbound

SABRE: A Multi-Agent Approach for Selecting Out-of-Distribution Detectors Under a Budget cites this paper.

SABRE: A Multi-Agent Approach for Selecting Out-of-Distribution Detectors Under a Budget Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T14:59:45.488563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54ff42bf-1d16-4158-8d76-377eebbad2ce · inbound

On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models cites this paper.

On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey

Reference 146

Resolution: unresolved; no resolver link, observed 2026-08-15T14:21:42.659516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.