Paper Citation Record · LEDGER

Addressing Bias in Generative AI: Challenges and Research Opportunities in Information Management

As of 11 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2502.10407.

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

pith.paper-citation-record.v1
2502.10407 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:51:18.110241Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

7 of 7 outbound references displayed

verified exact2
verified fuzzy0
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b55b21da-adda-4cd7-840a-d8181be817af · outbound

This paper cites Do Large Language Models Discriminate in Hiring Decisions on the Basis of Race, Ethnicity, and Gender?.

Addressing Bias in Generative AI: Challenges and Research Opportunities in Information Management Do Large Language Models Discriminate in Hiring Decisions on the Basis of Race, Ethnicity, and Gender?

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:18.084650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3350dc0-b417-4fc8-a169-3354bb2639e1 · outbound

This paper cites Evaluating Biases in Context-Dependent Health Questions.

Addressing Bias in Generative AI: Challenges and Research Opportunities in Information Management Evaluating Biases in Context-Dependent Health Questions

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-10T16:51:18.183288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 78f9cc00-05fc-4c5f-b14e-a42104977351 · outbound

This paper cites V., Wang, Z., Yin, Z., Hoang, N., Gonzalez, M., Quy, T.

Addressing Bias in Generative AI: Challenges and Research Opportunities in Information Management V., Wang, Z., Yin, Z., Hoang, N., Gonzalez, M., Quy, T

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:18.092391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 702c98d6-2d98-4b83-8140-21bbb5ff3be9 · outbound

This paper cites Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences.

Addressing Bias in Generative AI: Challenges and Research Opportunities in Information Management Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:18.110241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a2976ef-e2b0-4a30-8766-fda867e22458 · outbound

This paper cites Bias Neutralization Framework: Measuring Fairness in Large Language Models with Bias Intelligence Quotient (BiQ).

Addressing Bias in Generative AI: Challenges and Research Opportunities in Information Management Bias Neutralization Framework: Measuring Fairness in Large Language Models with Bias Intelligence Quotient (BiQ)

Reference 115

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T16:51:18.168150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 75c38a8e-9e28-4a34-bf8e-254f61c6b53f · outbound

This paper cites MABEL: Attenuating Gender Bias using Textual Entailment Data.

Addressing Bias in Generative AI: Challenges and Research Opportunities in Information Management MABEL: Attenuating Gender Bias using Textual Entailment Data

Reference 183

Resolution: verified exact; local_arxiv, observed 2026-08-10T16:51:18.197369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 49335da6-04c1-4189-8d95-a7882aed8873 · outbound

This paper cites an unresolved cited work.

Addressing Bias in Generative AI: Challenges and Research Opportunities in Information Management Unresolved cited work

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:18.089036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.