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Paper Citation Record · LEDGER

Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2401.15585.

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

pith.paper-citation-record.v1
2401.15585 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:21:28.290044Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T07:01:01.702275Z

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 38e4e138-40cb-4a08-b72c-c7af3ca6a78e · inbound

BiasFilter: An Inference-Time Debiasing Framework for Large Language Models cites this paper.

BiasFilter: An Inference-Time Debiasing Framework for Large Language Models Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T13:21:28.290044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:21:28.290044Z digest=sha256:dc81fa6a91062e1e4f5c3e691096607074047e96ccf9ba094df1c252d5022df1

Observation 7200a673-5290-4466-87d8-7dc2f35e7f2b · inbound

More or Less Wrong: A Benchmark for Directional Bias in LLM Comparative Reasoning cites this paper.

More or Less Wrong: A Benchmark for Directional Bias in LLM Comparative Reasoning Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T10:59:04.917391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:59:04.917391Z digest=sha256:122b1935d25a6d4b5fded9f0168e53bc82182b6e4c6d560c0dfc206b71609b23

Observation 2332d80b-b2c0-4c99-a2ea-c78009ee6401 · inbound

Guiding LLM Decision-Making with Fairness Reward Models cites this paper.

Guiding LLM Decision-Making with Fairness Reward Models Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T17:16:34.600067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:16:34.600067Z digest=sha256:3d2ca272d8de9f324522fa21651ee9d21a35cc0bd5f1b72e20447ca23e978571

Observation afccb6a7-8455-472e-8560-75bd902704e0 · inbound

Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM cites this paper.

Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

Reference 192

Resolution
unresolved
no resolver link, observed 2026-08-05T23:13:05.136314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:13:05.136314Z digest=sha256:c9ee23ba2d5b1e7744c3c4f112970538e8ebd586bc9c3eec143eb3e0bf793ada

Observation 6a076edf-6610-4ee9-ae13-9855612efb36 · inbound

Measuring Bias or Measuring the Task: Understanding the Brittle Nature of LLM Gender Biases cites this paper.

Measuring Bias or Measuring the Task: Understanding the Brittle Nature of LLM Gender Biases Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-05T10:16:43.181266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T10:16:43.181266Z digest=sha256:4185e243c34831c9d0696d937922f971fb4fe6c2351d9c6e4370c6b3560adca4

Observation e2528a84-987f-4eb0-826d-a00b4964d06c · inbound

Investigating Thinking Behaviours of Reasoning-Based Language Models for Social Bias Mitigation cites this paper.

Investigating Thinking Behaviours of Reasoning-Based Language Models for Social Bias Mitigation Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-18T07:01:01.705975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T06:56:33.427852Z digest=sha256:885c531cd5e4c5d9e115b7fa9860207f8c3613a1382361f621e473e062c64d87

Observation 0de6ad43-7130-42c8-b5ac-4482c0d87c7e · inbound

SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures cites this paper.

SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

Reference 37

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T16:36:08.888614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-09T15:56:52.689233Z digest=sha256:21f5fa9ffeaacda22e3d2cfbe5ef6fbafa365dac2287e193c514da90e3319466

Observation 342c7051-981b-49b3-9cff-387b9e7d1ac3 · inbound

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution cites this paper.

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T05:45:21.096810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-08T19:36:52.668048Z digest=sha256:5a7277a6347fccb56e8e24a2badd8966366a5ae6cd015b937d72be960cb9240f