Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Rapid Language Adaptation for Multilingual E2E Speech Recognition Using Encoder Prompting
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.12611.
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 2026-08-08T21:10:38.048273Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T11:52:13.704831Z
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 af33c653-2edc-4707-a890-be7c5e6dc7b3 · inbound
Evaluating Standard and Dialectal Frisian ASR: Multilingual Fine-tuning and Language Identification for Improved Low-resource Performance cites this paper.
Evaluating Standard and Dialectal Frisian ASR: Multilingual Fine-tuning and Language Identification for Improved Low-resource Performance Rapid Language Adaptation for Multilingual E2E Speech Recognition Using Encoder Prompting
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T21:10:38.048273Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea4af69f-db0d-4996-b02e-a97bae4e6ee7 · inbound
Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data cites this paper.
Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Rapid Language Adaptation for Multilingual E2E Speech Recognition Using Encoder Prompting
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:52:13.768823Z
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.