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Paper Citation Record · LEDGER

Text Clustering with Large Language Model Embeddings

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.15112.

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

pith.paper-citation-record.v1
2403.15112 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:34:03.392625Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T22:40:48.552790Z

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 b7660033-ed02-43e8-8b0c-cc33f87f2029 · inbound

A Dynamic Framework for Semantic Grouping of Common Data Elements (CDE) Using Embeddings and Clustering cites this paper.

A Dynamic Framework for Semantic Grouping of Common Data Elements (CDE) Using Embeddings and Clustering Text Clustering with Large Language Model Embeddings

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:03.392625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:03.392625Z digest=sha256:2a766f3fb09804204cf92c16e06d55627ce95fdb95f4d335e6be4106f8b71655

Observation bce1f1b0-f3c8-47b8-9f2e-f69f2936f645 · inbound

Can You Trust the Vectors in Your Vector Database? Black-Hole Attack from Embedding Space Defects cites this paper.

Can You Trust the Vectors in Your Vector Database? Black-Hole Attack from Embedding Space Defects Text Clustering with Large Language Model Embeddings

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:40:48.555400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T19:40:10.624513Z digest=sha256:1e80e919d23b4640c144096b8d4ca1890d699c2547734cd5729c25a66a815404

Observation fcea5a31-cd0b-4776-90f4-7be16807589d · inbound

Advanced Topic Modeling Techniques for Categorizing Software Vulnerabilities cites this paper.

Advanced Topic Modeling Techniques for Categorizing Software Vulnerabilities Text Clustering with Large Language Model Embeddings

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-11T23:15:06.472205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T23:15:06.472205Z digest=sha256:66192d7adb9b90febf56af61b97cefa7573b095c53af10490178c3aa6feccc15