Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2203.09122.
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 2026-08-03T06:30:56.289259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T04:13:36.849493Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-09T05:55:29.074033Z
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 4e466bcf-00f8-445a-a92c-dec6583b91fc · inbound
Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI cites this paper.
Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition
Reference 216
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T05:55:29.111668Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation dc88e0cf-2c58-41f6-b86e-3a3bbb96811c · inbound
What You Train Is What You Get: Gender Bias, Training Composition, and Post-Hoc Mitigation in Audio Deepfake Detection cites this paper.
What You Train Is What You Get: Gender Bias, Training Composition, and Post-Hoc Mitigation in Audio Deepfake Detection To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T14:47:58.592181Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f5c547b1-3def-4e7b-a24c-e290ec603850 · inbound
Simple Language Normalization Wins: Cross-Lingual Speaker Verification for the TidyVoice 2026 Challenge cites this paper.
Simple Language Normalization Wins: Cross-Lingual Speaker Verification for the TidyVoice 2026 Challenge To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T04:13:36.849493Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.