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Paper Citation Record · LEDGER

Enhancing Text Classification through LLM-Driven Active Learning and Human Annotation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.12114.

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

pith.paper-citation-record.v1
2406.12114 v1

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T14:38:36.213882Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 f9db89d4-e17d-4e5a-a9a6-0c5d133a3c4c · inbound

A Classifier That Teaches Itself: Self-Improving, Frozen-gate Training (SIFT) for Dynamic Document Classification cites this paper.

A Classifier That Teaches Itself: Self-Improving, Frozen-gate Training (SIFT) for Dynamic Document Classification Enhancing Text Classification through LLM-Driven Active Learning and Human Annotation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-01T16:44:39.246925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T16:44:39.246925Z digest=sha256:20bbfc25ced80fe45c3e9b92e9ee99ff7d2553c311fc8e28024aa1f085b59d64

Observation 6d430e2c-5404-4cfa-8266-e28377c4be7f · inbound

DocAnnot -- Accelerating the Creation of Key Information Extraction Datasets with GenAI-Powered Auto-annotation cites this paper.

DocAnnot -- Accelerating the Creation of Key Information Extraction Datasets with GenAI-Powered Auto-annotation Enhancing Text Classification through LLM-Driven Active Learning and Human Annotation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-02T14:38:36.213882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:38:36.213882Z digest=sha256:cc16a2bc1eed112baa9c5bc11ac50a4c87182880988e891608f1f322cf353e15