Paper Citation Record · LEDGER

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement

As of 10 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2506.22372.

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

pith.paper-citation-record.v1
2506.22372 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:11:52.902473Z

measured 55 of 55 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

verified exact3
verified fuzzy3
unresolved48
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 93cb607e-7210-4fd0-813e-d433f6b5bd44 · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T22:11:48.238741Z

Source-reported events for the cited work

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Observation 4c32d0ed-6a89-4f8f-b0ce-468ba35b0f9f · outbound

This paper cites Measuring Bias in a Ranked List using Term-based Representations.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Measuring Bias in a Ranked List using Term-based Representations

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:11:53.262146Z

Source-reported events for the cited work

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Observation 688a8933-8c53-4ee7-bd74-df28e56636bd · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 3

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Source-reported events for the cited work

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Observation 28664e28-0159-493d-b742-6831fe9784e6 · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 4

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Source-reported events for the cited work

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This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 5

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Observation 09b31fb8-74b3-400a-bb20-d9807c938387 · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T22:11:48.865176Z

Source-reported events for the cited work

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This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T22:11:48.965456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eee4f551-5653-494a-b276-a0793d02959a · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 9

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This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03333a40-8cac-4784-9cb5-d4db6ff1273c · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 11

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Source-reported events for the cited work

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Observation 6782ebb0-d735-4855-a932-efc86e0ba9ec · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:11:57.697615Z

Source-reported events for the cited work

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Observation f0a281fd-9a53-4474-847f-06db1f92537c · outbound

This paper cites Overview of the TREC 2022 Fair Ranking Track.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Overview of the TREC 2022 Fair Ranking Track

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:11:53.655284Z

Source-reported events for the cited work

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This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 14

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Source-reported events for the cited work

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Observation 8f42c474-a22e-48d6-98ca-44e263e815d1 · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 15

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 16

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Observation 2b411d2c-01bd-41a7-9eba-8c9968eb1559 · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 17

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 18

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 19

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This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 20

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 22

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Kumar, Saurav Sahay, Sahisnu Mazumder, Eda Okur, Ramesh Manuvinakurike, Nicole Beckage, Hsuan Su, Hung-yi Lee, and Lama Nachman

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 26

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This paper cites Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models.

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

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 30

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement In Find- ings of the Association for Computational Linguistics: EMNLP 2020 , Trevor Cohn, Yulan He, and Yang Liu (Eds.)

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Bowman, and Rachel Rudinger

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Quantifying the Impact of User Attention on Fair Group Representation in Ranked Lists

Reference 43

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 45

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Unavailable: canonical work link unavailable.

Observation 2e2ebbd5-eac2-4361-a9c4-ae5796c615df · outbound

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Observation 8910426d-b948-4bdb-892d-90ce6176d8b6 · outbound

This paper cites an unresolved cited work.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Nguyen, and Katrin Kirchhoff

Reference 48

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Unavailable: canonical work link unavailable.

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Measuring and Reducing Gendered Correlations in Pre-trained Models

Reference 54

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Unresolved cited work

Reference 1967

Resolution: unresolved; no resolver link, observed 2026-08-06T22:11:51.738060Z

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Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Information Processing & Management 57, 6 (2020), 102377

Reference 2020

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Observation 30bc8779-96b7-456a-ae13-09dd5332ab56 · outbound

This paper cites In International Conference on Machine Learning.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement In International Conference on Machine Learning

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:11:54.455043Z

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Observation f6d2a5e3-6d9b-48e0-b5e0-1141a96a4997 · outbound

This paper cites Can We Use Large Language Models to Fill Relevance Judgment Holes?.

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement Can We Use Large Language Models to Fill Relevance Judgment Holes?

Reference 2024

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Pith citing papers

No inbound Pith citation observations are available.