Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.14568.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T04:54:50.949266Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T11:01:31.970908Z
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 3b8dba37-0569-4a98-a88e-6db513a20450 · inbound
Measuring Diversity in Synthetic Datasets cites this paper.
Measuring Diversity in Synthetic Datasets LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition
Reference 83
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T04:54:50.949266Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 110aa6e9-78fb-4ec5-8c1f-5228c68bf326 · inbound
Prompt Candidates, then Distill: A Teacher-Student Framework for LLM-driven Data Annotation cites this paper.
Prompt Candidates, then Distill: A Teacher-Student Framework for LLM-driven Data Annotation LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition
Reference 9
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T11:01:32.025563Z
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.
Observation 5922a9a9-8648-4cf7-b116-e7b7d874fc53 · inbound
Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM cites this paper.
Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T00:55:00.014770Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.