Paper Citation Record · LEDGER

Semantic Anomaly Detection with Large Language Models

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.11307.

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

pith.paper-citation-record.v1
2305.11307 v2

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 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:10:22.654491Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:38:04.305611Z

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 e8dd82d9-88c8-4b0b-aa97-164e24a96558 · inbound

SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs cites this paper.

SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs Semantic Anomaly Detection with Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T11:14:08.521726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66147229-86a2-4f1f-ae29-83248c1dc728 · inbound

Vision Foundation Model Embedding-Based Semantic Anomaly Detection cites this paper.

Vision Foundation Model Embedding-Based Semantic Anomaly Detection Semantic Anomaly Detection with Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T22:10:22.654491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 205ed7d0-fc6d-4cb6-82f2-7aa67b0a3439 · inbound

Leveraging LLMs for Mission Planning in Precision Agriculture cites this paper.

Leveraging LLMs for Mission Planning in Precision Agriculture Semantic Anomaly Detection with Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T04:39:55.183083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9479fa28-744b-463e-8af7-be58b56596ee · inbound

One For All: LLM-based Heterogeneous Mission Planning in Precision Agriculture cites this paper.

One For All: LLM-based Heterogeneous Mission Planning in Precision Agriculture Semantic Anomaly Detection with Large Language Models

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:38:04.310927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.