Paper Citation Record · LEDGER

Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2408.03907.

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

pith.paper-citation-record.v1
2408.03907 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:22:15.244477Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T17:18:01.290616Z

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 b73ab64a-de91-4b7b-92e8-10e9699d09d8 · 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 Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T15:22:15.244477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f70d22c9-aea2-4a36-8890-b8dc1c1b4d7f · inbound

Mental Health Equity in LLMs: Leveraging Multi-Hop Question Answering to Detect Amplified and Silenced Perspectives cites this paper.

Mental Health Equity in LLMs: Leveraging Multi-Hop Question Answering to Detect Amplified and Silenced Perspectives Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:51.278122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4587c71-76ff-46aa-9ed3-a54e9a708008 · inbound

Bias, Accuracy, and Trust: Gender-Diverse Perspectives on Large Language Models cites this paper.

Bias, Accuracy, and Trust: Gender-Diverse Perspectives on Large Language Models Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:13.605542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55785f28-e42a-4eba-acb7-2612f45659d1 · inbound

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement cites this paper.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T22:11:50.660398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f3bf567-5443-4306-bb0c-82425943f1cc · inbound

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 169

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:35.916587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bbad25a-d8b6-4a33-86ba-0ba13fd3374e · inbound

LLMs on Trial: Evaluating Judicial Fairness for Large Language Models cites this paper.

LLMs on Trial: Evaluating Judicial Fairness for Large Language Models Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T17:29:44.217402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 816ce210-b669-4f68-81c4-49749a1a869f · inbound

Do Biased Models Have Biased Thoughts? cites this paper.

Do Biased Models Have Biased Thoughts? Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T22:39:24.845572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0f4982e-4841-493b-98f2-6664c5cbc809 · inbound

A Close Reading Approach to Gender Narrative Biases in AI-Generated Stories cites this paper.

A Close Reading Approach to Gender Narrative Biases in AI-Generated Stories Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T20:57:56.314890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 678451ca-4f1e-40b6-b44c-93aabbdefab1 · inbound

Quantifying Trust: Financial Risk Management for Trustworthy AI Agents cites this paper.

Quantifying Trust: Financial Risk Management for Trustworthy AI Agents Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:18:01.292780Z

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.

Observation f0f01230-a091-4032-9e45-2feaed959317 · inbound

Identifying Implicit Bias in LLM-based Chat AI Toward People with Intellectual Disabilities cites this paper.

Identifying Implicit Bias in LLM-based Chat AI Toward People with Intellectual Disabilities Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T11:02:29.180896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.