Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Semi-supervised transfer learning for language expansion of end-to-end speech recognition models to low-resource languages
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2111.10047.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:35:31.355137Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T05:30:23.456663Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
2
pith, observed 2026-08-10T05:30:23.456663Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation ddf13c9c-6d43-4bed-b581-db67a5daf45f · inbound
Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages cites this paper.
Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages Semi-supervised transfer learning for language expansion of end-to-end speech recognition models to low-resource languages
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T23:35:32.986393Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.