Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Beyond Binary Gender Labels: Revealing Gender Biases in LLMs through Gender-Neutral Name Predictions
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.05271.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:22:18.344953Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T15:02:35.331930Z
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 de3d2f05-56de-4786-b75c-6af2967fb496 · inbound
LFTF: Locating First and Then Fine-Tuning for Mitigating Gender Bias in Large Language Models cites this paper.
LFTF: Locating First and Then Fine-Tuning for Mitigating Gender Bias in Large Language Models Beyond Binary Gender Labels: Revealing Gender Biases in LLMs through Gender-Neutral Name Predictions
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:22:18.344953Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7e1ff625-984d-4233-b716-53f75edd6be8 · inbound
Obscured but Not Erased: Evaluating Nationality Bias in LLMs via Name-Based Bias Benchmarks cites this paper.
Obscured but Not Erased: Evaluating Nationality Bias in LLMs via Name-Based Bias Benchmarks Beyond Binary Gender Labels: Revealing Gender Biases in LLMs through Gender-Neutral Name Predictions
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:02:35.337072Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.