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Paper Citation Record · LEDGER

Semantic Anomaly Detection with Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 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 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:39:55.183083Z

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 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.

source=pdf_text observed=2026-08-07T04:39:55.183083Z digest=sha256:fd7a5e8d23d85417c5278d77ee9a3da42872cc6d76ce803d35adb7dbf56770a5

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T04:38:03.948684Z digest=sha256:8e129b1536307836e4202a11c692675bd6a35f1f3b8b348ecfbb80a632a796ee