Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.14086.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T06:03:43.964858Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T18:57:50.091958Z
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 07bc4d9b-a123-4fe5-9c8f-3da2999d5972 · inbound
Unsupervised Bilingual Lexicon Induction for Low Resource Languages cites this paper.
Unsupervised Bilingual Lexicon Induction for Low Resource Languages LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T06:03:43.964858Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b525f05b-e5b1-4185-8a28-ac6daa48002d · inbound
WARDEN: Endangered Indigenous Language Transcription and Translation with 6 Hours of Training Data cites this paper.
WARDEN: Endangered Indigenous Language Transcription and Translation with 6 Hours of Training Data LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T18:57:50.094140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.