Pith. sign in

Paper Citation Record · LEDGER

Adapting an ASR Foundation Model for Spoken Language Assessment

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.09378.

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

pith.paper-citation-record.v1
2307.09378 v2

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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:12:55.564620Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T20:42:49.439712Z

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 6a6e6dca-34bd-4142-bd72-325e3d9d08c6 · inbound

Fine-tuning Whisper on Low-Resource Languages for Real-World Applications cites this paper.

Fine-tuning Whisper on Low-Resource Languages for Real-World Applications Adapting an ASR Foundation Model for Spoken Language Assessment

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T11:12:55.564620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:12:55.564620Z digest=sha256:cf0eb03f51219d50d0d228bf0125d63e0726f261fcb1b38e878f01013464d4a6

Observation e95b8b6c-1347-486e-a312-0f93bfc6adb0 · inbound

Which one Performs Better? Wav2Vec or Whisper? Applying both in Badini Kurdish Speech to Text (BKSTT) cites this paper.

Which one Performs Better? Wav2Vec or Whisper? Applying both in Badini Kurdish Speech to Text (BKSTT) Adapting an ASR Foundation Model for Spoken Language Assessment

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-05T20:42:49.553835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-05T20:42:48.294494Z digest=sha256:665f11c989c4a6c55e49afc0bf953800fa1fd6360e8329ee49fa97e56a4392c4