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Paper Citation Record · LEDGER

Bias and Fairness in Large Language Models: A Survey

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 43 inbound Pith citation observations for arXiv:2309.00770.

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

pith.paper-citation-record.v1
2309.00770 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 43 of 43 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:30:20.033778Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

59
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3af74d44-db1c-4c97-b70a-30a7325b8887 · inbound

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models cites this paper.

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models Bias and Fairness in Large Language Models: A Survey

Reference 126

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arxiv_id, observed 2026-05-13T13:43:11.187231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-13T13:43:11.024069Z digest=sha256:411092be192db1c3627b453a18af7f746f63a596404acf1b7584be60aa1f40fa

Observation 944c1e76-f9a3-4b54-a063-05aace72f3f5 · inbound

The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey cites this paper.

The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey Bias and Fairness in Large Language Models: A Survey

Reference 6

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arxiv_id, observed 2026-05-16T23:16:41.718292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T23:16:41.679855Z digest=sha256:aca29bca1ba25631576be46098e904a7f06081f727b848fe0ec2d158aba3a7fb

Observation a0bbc96c-6489-4c0f-88a4-bd508b0c23e0 · inbound

A Survey on the Memory Mechanism of Large Language Model based Agents cites this paper.

A Survey on the Memory Mechanism of Large Language Model based Agents Bias and Fairness in Large Language Models: A Survey

Reference 60

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arxiv_id, observed 2026-05-15T07:21:39.873541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-15T07:21:39.440092Z digest=sha256:180b5b3e7b26327f286dc237960ffc8abbd2111d2de2cd1d8e57906f69d19575

Observation 31eecd68-837a-4cb9-a7d8-68c7172a4bf4 · inbound

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions cites this paper.

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions Bias and Fairness in Large Language Models: A Survey

Reference 222

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arxiv_id, observed 2026-05-23T21:55:50.238919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-23T21:54:26.670284Z digest=sha256:3d99babf4be9f51c13f503d6de1b9ff066d1b4ce3bc8f3c85a467192ae0ac0ed

Observation 78e9d8bb-aa2f-4481-8285-8eca50e402cc · inbound

Safety case template for frontier AI: A cyber inability argument cites this paper.

Safety case template for frontier AI: A cyber inability argument Bias and Fairness in Large Language Models: A Survey

Reference 26

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no resolver link, observed 2026-08-12T22:01:11.336200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T22:01:11.336200Z digest=sha256:a8c904e45fbff3458c58c20686ec01014f9290ea06022f9d440f8b535c21afa2

Observation 0d1ba4de-a69e-45f8-97b0-2c43c6cd2da5 · inbound

Bias Unveiled: Investigating Social Bias in LLM-Generated Code cites this paper.

Bias Unveiled: Investigating Social Bias in LLM-Generated Code Bias and Fairness in Large Language Models: A Survey

Reference 14

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no resolver link, observed 2026-08-12T19:46:44.536437Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-12T19:46:44.536437Z digest=sha256:4ae9aceb8834eec3d96dfd6d9788a54ca76e092fb7893d323f5adb523a99e482

Observation 288f2c6c-6045-464a-9794-07a6034ed886 · inbound

Unveiling Performance Challenges of Large Language Models in Low-Resource Healthcare: A Demographic Fairness Perspective cites this paper.

Unveiling Performance Challenges of Large Language Models in Low-Resource Healthcare: A Demographic Fairness Perspective Bias and Fairness in Large Language Models: A Survey

Reference 9

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no resolver link, observed 2026-08-12T05:18:55.756959Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:18:55.756959Z digest=sha256:87e35d9aff9d765084bf0fc9ea8cf30fb06a2bdbe13038ad89208c9e7fac0ae6

Observation 8fdc91a2-0a02-4aae-b8eb-ce31aab48bd3 · inbound

Best Practices for Large Language Models in Radiology cites this paper.

Best Practices for Large Language Models in Radiology Bias and Fairness in Large Language Models: A Survey

Reference 45

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no resolver link, observed 2026-08-12T04:35:59.376378Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T04:35:59.376378Z digest=sha256:a69680d729caa8cff51bfac9cf7e550cf39c83f5ab4bf6596c149a7f821b5b36

Observation 5b62a655-9e91-4f45-a9bd-e53ffa61f0f4 · inbound

Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges cites this paper.

Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges Bias and Fairness in Large Language Models: A Survey

Reference 31

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no resolver link, observed 2026-08-11T22:41:14.204747Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:41:14.204747Z digest=sha256:a0b9743d3c53434ce6146601ad3de6f1cfa3e426c90e0cfb963ff10da9f33654

Observation be77ffde-d3c5-4915-968b-368b2febfbc3 · inbound

Improving Linguistic Diversity of Large Language Models with Possibility Exploration Fine-Tuning cites this paper.

Improving Linguistic Diversity of Large Language Models with Possibility Exploration Fine-Tuning Bias and Fairness in Large Language Models: A Survey

Reference 9

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no resolver link, observed 2026-08-11T22:34:22.627897Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:34:22.627897Z digest=sha256:32f1e24252204ec26b4d1c86ec508b5f88fb12bc747918b74b648415bac1a1a1

Observation 3a690209-2f9a-48e4-bd28-6d01caf4ec52 · inbound

LangFair: A Python Package for Assessing Bias and Fairness in Large Language Model Use Cases cites this paper.

LangFair: A Python Package for Assessing Bias and Fairness in Large Language Model Use Cases Bias and Fairness in Large Language Models: A Survey

Reference 8

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no resolver link, observed 2026-08-10T21:56:29.713205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:56:29.713205Z digest=sha256:5c96bfafe4c466a8af027a479c59ad033efca3fdbe972172681b0d8328c38463

Observation 4567e7c4-f835-498b-8002-3b784d315e50 · inbound

Unveiling Behavioral Differences in Bilingual Information Operations: A Network-Based Approach cites this paper.

Unveiling Behavioral Differences in Bilingual Information Operations: A Network-Based Approach Bias and Fairness in Large Language Models: A Survey

Reference 10

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no resolver link, observed 2026-08-10T21:31:38.551463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:31:38.551463Z digest=sha256:30040d8cdbf0db7bb122767d29d8996fe0ae75f3118ab8894e2ecbb024a57151

Observation f096aea0-374c-44db-8bb0-e311cecdf81c · inbound

An Empirically-grounded tool for Automatic Prompt Linting and Repair: A Case Study on Bias, Vulnerability, and Optimization in Developer Prompts cites this paper.

An Empirically-grounded tool for Automatic Prompt Linting and Repair: A Case Study on Bias, Vulnerability, and Optimization in Developer Prompts Bias and Fairness in Large Language Models: A Survey

Reference 22

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no resolver link, observed 2026-08-10T17:14:06.550646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:14:06.550646Z digest=sha256:ba1776ca9936e390ebaf59e56ff4ef7cc777e621301d1694728e854811e486d7

Observation bb318c4f-8fc2-451f-91d1-b1f95367d5fe · inbound

Option-ID Based Elimination For Multiple Choice Questions cites this paper.

Option-ID Based Elimination For Multiple Choice Questions Bias and Fairness in Large Language Models: A Survey

Reference 7

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no resolver link, observed 2026-08-10T14:35:58.859322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:35:58.859322Z digest=sha256:87c8de1a6bdb5abe1a2de8bf9e033b0e00dba6bd8e34579213344434684acfab

Observation 90ef5c30-f1b9-4f1b-9e8f-0cb0a1b344b2 · inbound

Comparing Human and LLM Generated Code: The Jury is Still Out! cites this paper.

Comparing Human and LLM Generated Code: The Jury is Still Out! Bias and Fairness in Large Language Models: A Survey

Reference 8

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no resolver link, observed 2026-08-10T10:11:10.773254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:11:10.773254Z digest=sha256:d4bf64e22be1abe9801aa1b37ccc6e5886e514f7d86e11a69366c19fc26048d7

Observation 8a044bcd-c045-409c-869e-a908f5a06929 · inbound

CollabLLM: From Passive Responders to Active Collaborators cites this paper.

CollabLLM: From Passive Responders to Active Collaborators Bias and Fairness in Large Language Models: A Survey

Reference 15

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no resolver link, observed 2026-08-09T18:18:09.115455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:18:09.115455Z digest=sha256:05f41eb5637f9ad1c195dd657cf426e2ae61575848eba47d59cba43f3f39636d

Observation 3e61e840-0b80-481a-acc2-9e8ad0bdf21d · inbound

Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applications cites this paper.

Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applications Bias and Fairness in Large Language Models: A Survey

Reference 29

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no resolver link, observed 2026-08-09T17:43:55.469259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T17:43:55.469259Z digest=sha256:f9eb59017c1c058a6d9188838d9c885a446f74407876698b53c0e2dab38c0812

Observation 5820b242-7320-46b4-939d-13a30dd93092 · inbound

Feeding LLM Annotations to BERT Classifiers at Your Own Risk cites this paper.

Feeding LLM Annotations to BERT Classifiers at Your Own Risk Bias and Fairness in Large Language Models: A Survey

Reference 12

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no resolver link, observed 2026-08-16T11:30:20.033778Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:30:20.033778Z digest=sha256:f4dfb80ba051916e19847a4e3147d4f12b4f50452b4109717f7b26acc3abf0cd

Observation 9cab6712-cc5e-4532-b1e8-ca714e54eceb · inbound

A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigms cites this paper.

A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigms Bias and Fairness in Large Language Models: A Survey

Reference 256

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no resolver link, observed 2026-08-16T11:07:59.424245Z

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source=pdf_text observed=2026-08-16T11:07:59.424245Z digest=sha256:357c9d43857a863d8f3ecf8c5f565008eb778009e63bb0cb7698cc1daf251ecf

Observation 1ad7db4e-fd78-4b5b-bcad-0865ad4bc9f1 · inbound

Justified Evidence Collection for Argument-based AI Fairness Assurance cites this paper.

Justified Evidence Collection for Argument-based AI Fairness Assurance Bias and Fairness in Large Language Models: A Survey

Reference 12

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no resolver link, observed 2026-08-15T22:07:58.708664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:07:58.708664Z digest=sha256:baf05069245676d99a65c5679c2dea5bfe76b68d2741954cabdb01b6bbb5472a

Observation 41f36054-e888-4b06-b806-ae23b8c0dcef · inbound

A Framework for Auditing Chatbots for Dialect-Based Quality-of-Service Harms cites this paper.

A Framework for Auditing Chatbots for Dialect-Based Quality-of-Service Harms Bias and Fairness in Large Language Models: A Survey

Reference 33

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no resolver link, observed 2026-08-07T10:46:33.477228Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:46:33.477228Z digest=sha256:2a4e8e656fc58f73f299a0f7c6dd89ebfc3772084e95d2b8c270cf0e531b12ea

Observation 5315fa85-2d08-4d40-a3ca-f0f4e641d115 · inbound

Adultification Bias in LLMs and Text-to-Image Models cites this paper.

Adultification Bias in LLMs and Text-to-Image Models Bias and Fairness in Large Language Models: A Survey

Reference 29

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no resolver link, observed 2026-08-07T05:42:53.344745Z

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source=pdf_text observed=2026-08-07T05:42:53.344745Z digest=sha256:eec11b5428f1ac49969d914f4e355cef6cb8de420f7802d8dac2b1ce2f27dfa0

Observation 9ac79af2-8955-4e80-8e72-19b881aba6d1 · inbound

Explicit Preference Optimization: No Need for an Implicit Reward Model cites this paper.

Explicit Preference Optimization: No Need for an Implicit Reward Model Bias and Fairness in Large Language Models: A Survey

Reference 19

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no resolver link, observed 2026-08-07T05:40:17.886568Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:40:17.886568Z digest=sha256:885762af68cec349ba09de450fddb70fc552d725df6d467fd388c7614c4455a7

Observation 898687bb-6337-47f7-a1a2-9f55ce94871a · inbound

A quantum semantic framework for natural language processing cites this paper.

A quantum semantic framework for natural language processing Bias and Fairness in Large Language Models: A Survey

Reference 78

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no resolver link, observed 2026-08-07T04:40:10.021463Z

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source=pdf_text observed=2026-08-07T04:40:10.021463Z digest=sha256:8d15846866cf35af33885462e22931afcc5d08715f4d78bb258e12d63d655c30

Observation 78e7071f-6899-4726-8d4d-245f880fdbe3 · inbound

Are Bias Evaluation Methods Biased ? cites this paper.

Are Bias Evaluation Methods Biased ? Bias and Fairness in Large Language Models: A Survey

Reference 2024

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no resolver link, observed 2026-08-15T19:14:19.804344Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:14:19.804344Z digest=sha256:7180f884a2ed07466774cd73b926015165eefa80ab3b134f00cc6dc73e126504

Observation 7cc77384-aa30-4f4a-be71-f7745a98b725 · inbound

Exploring Gender Bias Beyond Occupational Titles cites this paper.

Exploring Gender Bias Beyond Occupational Titles Bias and Fairness in Large Language Models: A Survey

Reference 15

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no resolver link, observed 2026-08-06T20:28:16.588403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:28:16.588403Z digest=sha256:b6bf6b3f5489e1c884e0b3020d8a9ac561dd284085e967ed38e0590833418559

Observation 790ed743-73eb-441e-be4c-a6a5cf2cf37c · inbound

WETBench: A Benchmark for Detecting Task-Specific Machine-Generated Text on Wikipedia cites this paper.

WETBench: A Benchmark for Detecting Task-Specific Machine-Generated Text on Wikipedia Bias and Fairness in Large Language Models: A Survey

Reference 3

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no resolver link, observed 2026-08-06T20:20:02.699551Z

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source=pdf_text observed=2026-08-06T20:20:02.699551Z digest=sha256:75eecbbde07765357edd0ee946deb75892672eebf82a85a68c0731e08b35cc5b

Observation 4ecffbf0-0783-475e-a7c3-b963a9146042 · inbound

Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering cites this paper.

Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering Bias and Fairness in Large Language Models: A Survey

Reference 20

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no resolver link, observed 2026-08-06T17:43:53.690982Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:43:53.690982Z digest=sha256:a7dc453d6a2cd306346f8ed1882ba18c1e56a1055aae801b66940cf8b2a14790

Observation 8a8a640f-38fc-4591-935f-35ff28a86700 · inbound

Trustworthy Reasoning: Evaluating and Enhancing Factual Accuracy in LLM Intermediate Thought Processes cites this paper.

Trustworthy Reasoning: Evaluating and Enhancing Factual Accuracy in LLM Intermediate Thought Processes Bias and Fairness in Large Language Models: A Survey

Reference 46

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no resolver link, observed 2026-08-15T18:03:15.244043Z

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source=pdf_text observed=2026-08-15T18:03:15.244043Z digest=sha256:06b1f3d177ae37661e62926e7d594d39ea7e912ec29e7f44b747d8c2dd89f687

Observation 7e2dfbe5-f929-45c6-ad0a-786c7a9b4a94 · inbound

Trustworthy Reasoning: Evaluating and Enhancing Factual Accuracy in LLM Intermediate Thought Processes cites this paper.

Trustworthy Reasoning: Evaluating and Enhancing Factual Accuracy in LLM Intermediate Thought Processes Bias and Fairness in Large Language Models: A Survey

Reference 47

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no resolver link, observed 2026-08-15T18:03:15.248522Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:03:15.248522Z digest=sha256:fc9adb35cfd6faf0c32432b4b5a1216fc52eeba3b021e7ccbeb186f7eec6fcf0

Observation 635ee3e4-2704-47be-a65f-114898fb683e · 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 Bias and Fairness in Large Language Models: A Survey

Reference 7

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no resolver link, observed 2026-08-05T20:57:56.188933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:57:56.188933Z digest=sha256:ea8178c2b696dc399d17ec7d192396c8eb337bd5090a3d666c6084f82b0643a6

Observation 8240b4a1-9656-4ce6-9471-2a2d19004a0c · inbound

Guidelines for Empirical Studies in Software Engineering involving Large Language Models cites this paper.

Guidelines for Empirical Studies in Software Engineering involving Large Language Models Bias and Fairness in Large Language Models: A Survey

Reference 39

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verified exact
arxiv_id, observed 2026-05-18T22:02:52.211601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-18T22:02:36.307598Z digest=sha256:25931a02e2b36f8d4f50a4e8f4a3b1d6097959d192308351d3219f5afa465c78

Observation a938ae3b-b563-48ab-8314-d5412a0fe066 · inbound

Guidelines for Empirical Studies in Software Engineering involving Large Language Models cites this paper.

Guidelines for Empirical Studies in Software Engineering involving Large Language Models Bias and Fairness in Large Language Models: A Survey

Reference 39

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arxiv_id, observed 2026-05-25T08:20:31.379898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-25T08:18:18.448122Z digest=sha256:e0d30fba825b7eeb49350a2c42639204efb0727e74da8eb4885eb189730cc917

Observation eeb89a5d-63e5-44d1-a2e9-a622ed6c7436 · inbound

Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework cites this paper.

Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework Bias and Fairness in Large Language Models: A Survey

Reference 14

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verified exact
arxiv_id, observed 2026-05-18T18:16:43.769596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-18T18:13:01.662828Z digest=sha256:f3f658d211554ecfaee50f9b2bbc876bf7a748d11237700591d7c31419bc59f0

Observation 02d0808c-8d3a-4a62-b393-bca86a6ffce2 · inbound

Saying More Than They Know: A Framework for Quantifying Epistemic-Rhetorical Miscalibration in Large Language Models cites this paper.

Saying More Than They Know: A Framework for Quantifying Epistemic-Rhetorical Miscalibration in Large Language Models Bias and Fairness in Large Language Models: A Survey

Reference 1

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metadata mismatch
arxiv_id, observed 2026-05-15T00:28:22.970065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-15T00:25:04.460757Z digest=sha256:146d019c5ded124b8edcdbc8505409c684bcd610e7ab6e9c249e7a74f8253bf0

Observation 0097e688-5275-4446-a744-a7ed7533811e · inbound

Social Bias in LLM-Generated Code: Benchmark and Mitigation cites this paper.

Social Bias in LLM-Generated Code: Benchmark and Mitigation Bias and Fairness in Large Language Models: A Survey

Reference 150

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arxiv_id, observed 2026-05-11T15:36:08.592359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-09T19:34:51.433422Z digest=sha256:6d81dd1719102757697118922b34d39614c041c82ee2ade5816ccb0161763efe

Observation 246a6c2f-2453-473c-aa47-6c93ad1b3370 · inbound

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning cites this paper.

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning Bias and Fairness in Large Language Models: A Survey

Reference 86

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T21:52:48.312667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-19T21:49:07.440832Z digest=sha256:ed19fb1a7701743b3097ff4dcc630d21d140dec88fc685aa0c0c1a3dc2131856

Observation dab4f06e-a858-471a-b6b1-2935faf48b92 · inbound

Mixed-Modality Dual Face-Hair Retrieval cites this paper.

Mixed-Modality Dual Face-Hair Retrieval Bias and Fairness in Large Language Models: A Survey

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:46:28.466501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-28T10:40:37.283129Z digest=sha256:b8e7ad6908b9867cbbcaba6c6538bf769ad39aeda7e87a050ee35b34b58b91ea

Observation 91922207-7be3-4b5e-be85-87c2052325c7 · inbound

AgentFairBench: Do LLM Agents Discriminate When They Act? cites this paper.

AgentFairBench: Do LLM Agents Discriminate When They Act? Bias and Fairness in Large Language Models: A Survey

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:38:44.501626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T03:53:38.554457Z digest=sha256:12b1b3412f991493ce8e1058da60daa6f40eefd161580bdffde4c47d053b004a

Observation cbec5595-dc24-4850-99da-b85f56063b72 · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems Bias and Fairness in Large Language Models: A Survey

Reference 165

Resolution
verified exact
arxiv_id, observed 2026-07-04T11:09:46.361178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T08:09:57.542558Z digest=sha256:a681932b18856d4970bdbed6c93a7654117c31c685bda3a724bbb5f64d286a67

Observation 4a5ca330-0535-4435-a318-0dbdda6217d4 · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems Bias and Fairness in Large Language Models: A Survey

Reference 153

Resolution
unresolved
no resolver link, observed 2026-08-02T10:27:18.338457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:27:18.338457Z digest=sha256:661a4e482ffb726e51cc90631ea4d5190bb21f165ab8f9cc04853286ab545e3b

Observation d3460a43-df54-4ffc-82ee-5622eb6b6b9b · inbound

Auditing LLM-Governed Social Robots with Culture-Specific Moral Gradients cites this paper.

Auditing LLM-Governed Social Robots with Culture-Specific Moral Gradients Bias and Fairness in Large Language Models: A Survey

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-06-30T11:14:37.479993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T11:13:36.521513Z digest=sha256:1de060890e668b8f8d36eec4e08c8a4eb3ac2db4d2d85e954bd66960936c605e

Observation f9fa35a9-d8ce-4fc6-b74e-10aa60c59233 · inbound

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning cites this paper.

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning Bias and Fairness in Large Language Models: A Survey

Reference 159

Resolution
unresolved
no resolver link, observed 2026-08-15T14:17:57.065179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:17:57.065179Z digest=sha256:5d30b3bbaa7b174a91997b312ec5b4c5f74d46059be19b77957bcb493e5bba5c