Paper Citation Record · LEDGER

Data and AI governance: Promoting equity, ethics, and fairness in large language models

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2508.03970.

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

pith.paper-citation-record.v1
2508.03970 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T01:03:24.414956Z

measured 38 of 38 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 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

38 of 38 outbound references displayed

verified exact8
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce15dd3a-77bf-4d0a-b748-a08b790ac5e3 · outbound

This paper cites an unresolved cited work.

Data and AI governance: Promoting equity, ethics, and fairness in large language models Unresolved cited work

Reference 1

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This paper cites title Generative AI to become a \ 1.3 trillion market by 2032, research finds ( year 2023 ).

Data and AI governance: Promoting equity, ethics, and fairness in large language models title Generative AI to become a \ 1.3 trillion market by 2032, research finds ( year 2023 )

Reference 2

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Observation 86d15621-3ae8-440a-9312-d48c5039630a · outbound

This paper cites BEATS: Bias Evaluation and Assessment Test Suite for Large Language Models.

Data and AI governance: Promoting equity, ethics, and fairness in large language models BEATS: Bias Evaluation and Assessment Test Suite for Large Language Models

Reference 3

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Observation 104d92ad-dd58-4db8-a0bb-a1c1d23dccc7 · outbound

This paper cites title Worldwide spending on artificial intelligence forecast to reach \ 632 billion in 2028 ( year 2023 ).

Data and AI governance: Promoting equity, ethics, and fairness in large language models title Worldwide spending on artificial intelligence forecast to reach \ 632 billion in 2028 ( year 2023 )

Reference 4

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This paper cites title Generative AI market forecasts revised upward to \ 52.2b by 2028 ( year 2023 ).

Data and AI governance: Promoting equity, ethics, and fairness in large language models title Generative AI market forecasts revised upward to \ 52.2b by 2028 ( year 2023 )

Reference 5

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Observation c0e4ada4-b9d2-465b-9c93-a4cc13c7101d · outbound

This paper cites title Generative AI spending to reach \ 26 billion by 2027 ( year 2023 ).

Data and AI governance: Promoting equity, ethics, and fairness in large language models title Generative AI spending to reach \ 26 billion by 2027 ( year 2023 )

Reference 6

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This paper cites title Generative AI market size, share, and trends 2024 to 2033 ( year 2023 ).

Data and AI governance: Promoting equity, ethics, and fairness in large language models title Generative AI market size, share, and trends 2024 to 2033 ( year 2023 )

Reference 7

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This paper cites title Spend on generative AI will grow 36\ note Online: https://www.forrester.com/blogs/spend-on-generative-ai-will-grow-36-annually-to-2030/.

Data and AI governance: Promoting equity, ethics, and fairness in large language models title Spend on generative AI will grow 36\ note Online: https://www.forrester.com/blogs/spend-on-generative-ai-will-grow-36-annually-to-2030/

Reference 8

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Observation 3c95cd0a-b328-46cb-b770-3619433715d4 · outbound

This paper cites , author Hu, Q.

Data and AI governance: Promoting equity, ethics, and fairness in large language models , author Hu, Q

Reference 9

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Observation 2ec95ab2-e509-45b2-99c9-943fe61204fd · outbound

This paper cites & author Alhashmi, S.

Data and AI governance: Promoting equity, ethics, and fairness in large language models & author Alhashmi, S

Reference 10

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Observation 5475edd2-8c7f-4878-818a-f924bcc2e803 · outbound

This paper cites Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings.

Data and AI governance: Promoting equity, ethics, and fairness in large language models Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings

Reference 11

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Data and AI governance: Promoting equity, ethics, and fairness in large language models , author Tan, I

Reference 12

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Unresolved cited work

Reference 13

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Data and AI governance: Promoting equity, ethics, and fairness in large language models , author Cai, X

Reference 14

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Unresolved cited work

Reference 16

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Data and AI governance: Promoting equity, ethics, and fairness in large language models , author Lin, E

Reference 17

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Observation 12380f44-eb76-4955-9ee5-ac7d8b7a4700 · outbound

This paper cites Promises and pitfalls of artificial intelligence for legal applications.

Data and AI governance: Promoting equity, ethics, and fairness in large language models Promises and pitfalls of artificial intelligence for legal applications

Reference 18

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 19

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Data and AI governance: Promoting equity, ethics, and fairness in large language models , author Janssen, M

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Data and AI governance: Promoting equity, ethics, and fairness in large language models , author Agdas, D

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Unresolved cited work

Reference 22

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This paper cites title The Basel Committee on Banking Supervision: A History of the Early Years, 1974--1997 ( publisher Cambridge University Press , year 2011 ).

Data and AI governance: Promoting equity, ethics, and fairness in large language models title The Basel Committee on Banking Supervision: A History of the Early Years, 1974--1997 ( publisher Cambridge University Press , year 2011 )

Reference 23

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This paper cites title Iso 14001 - environmental management systems — requirements with guidance for use.

Data and AI governance: Promoting equity, ethics, and fairness in large language models title Iso 14001 - environmental management systems — requirements with guidance for use

Reference 24

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This paper cites The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence.

Data and AI governance: Promoting equity, ethics, and fairness in large language models The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence

Reference 25

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Ethical and social risks of harm from Language Models

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Data and AI governance: Promoting equity, ethics, and fairness in large language models , author Al-Mallah, M

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Fairness Assessment for Artificial Intelligence in Financial Industry

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Data and AI governance: Promoting equity, ethics, and fairness in large language models title Explainable artificial intelligence ( year 2017 )

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Data and AI governance: Promoting equity, ethics, and fairness in large language models A Unified Approach to Interpreting Model Predictions

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Data and AI governance: Promoting equity, ethics, and fairness in large language models "Why Should I Trust You?": Explaining the Predictions of Any Classifier

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Explaining Hyperparameter Optimization via Partial Dependence Plots

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Counterfactual Explanations for Machine Learning: Challenges Revisited

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

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Data and AI governance: Promoting equity, ethics, and fairness in large language models Attention Is All You Need

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Pith citing papers

No inbound Pith citation observations are available.