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Paper Citation Record · LEDGER

A Contrastive Learning Approach to Mitigate Bias in Speech Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.14686.

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

pith.paper-citation-record.v1
2406.14686 v1

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:20:38.913978Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T16:16:15.082429Z

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 85b739f4-f93a-4297-bfc4-a9f9b84cc2e2 · inbound

Paying Alignment Tax with Contrastive Learning cites this paper.

Paying Alignment Tax with Contrastive Learning A Contrastive Learning Approach to Mitigate Bias in Speech Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:20:38.913978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:20:38.913978Z digest=sha256:d0cf9a50504c17785fe95ccca9b44015bbfa29ee102a66e791afa9068b6c07b8

Observation 660c25d1-0ac0-48b8-97b5-be2e4ed25632 · inbound

Bias In, Bias Out? Finding Unbiased Subnetworks in Vanilla Models cites this paper.

Bias In, Bias Out? Finding Unbiased Subnetworks in Vanilla Models A Contrastive Learning Approach to Mitigate Bias in Speech Models

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-15T16:16:15.086529Z

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.

source=pdf_text observed=2026-05-15T16:14:35.756456Z digest=sha256:968029a78de04482d22d1814aa3e6c464b84415edf29d49d403a8351572c5a54