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Paper Citation Record · LEDGER

Bias and Fairness in Large Language Models: A Survey

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 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 25 of 25 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 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:18:09.115455Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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

Resolution
metadata mismatch
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T13:43:11.024069Z digest=sha256:7e81bc9f0ab8b523de1060a37953853b537bd31f8da81676473abcfc05545fe8

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

Resolution
verified exact
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T23:16:41.679855Z digest=sha256:230b02f57473a889cf376c5067d66588193532abbd9b521d0220ffddb3c61dff

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

Resolution
metadata mismatch
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T07:21:39.440092Z digest=sha256:8df862975d102d534d67293b1da771af781f7f8a1c9e9f850afa624c102e1eef

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

Resolution
verified exact
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T21:54:26.670284Z digest=sha256:544e38744e61292c08392243dcd4ae164f33c0b6fea871fed731f9fcbd5efa6c

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

Resolution
unresolved
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=sha256:86e280abf902cc87c986337ae52d2b80a925a475da0d71b64a5a7c2d64a7d7fe

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

Resolution
unresolved
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:b129487373e84025ea5de4c37adffcf1d4df6d220c1485841e3d1478b9c8a3c0

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:46:33.477228Z digest=sha256:b6e0631b21db1f0c15449d1b5e449c5c634902264f3a359ebcf577aa39ab9505

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:42:53.344745Z digest=sha256:25399f0532e9b0d72d61e9f524d1d3083016257af9eff2d80558588fb3db7361

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:40:17.886568Z digest=sha256:f12a515212872080a08852c8169de3de94ee72b173b1d0b34e93694141e7261c

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:40:10.021463Z digest=sha256:865eb38ae88354a71eff1f1fa5484e610d1a3ed6afaa6b19e245cef0fdc2f91d

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

Resolution
unresolved
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=sha256:0fef9a0a826af2a155192aad9d2eaf2af763e41caae5168dbbf76b9ff403bcf5

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:20:02.699551Z digest=sha256:5130c957afbf2ce786131716cb1a8725d4587e05de621fffed86e8293bbee2d5

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:43:53.690982Z digest=sha256:5be3717f6ac00a18d0b0097ff0e8831e89ab88de558311b25bc6dc5be75971de

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

Resolution
unresolved
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=sha256:40cde95b41e2340223e86742cc629e8e786801d8d71780e043d3db7c788958f8

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T22:02:36.307598Z digest=sha256:b5b2cce36e421129c4eb132cc316704d16c013f1915e4dee8d38421be7f6fc26

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

Resolution
verified exact
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T08:18:18.448122Z digest=sha256:0975fd58cd163bcc09d35e06e1c01b49da4107f38899a4b9734fe079d8d11e2c

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-18T18:13:01.662828Z digest=sha256:275e914c7bc0916ba262bdadb9d45759968937760a667f96322f33f8b28bea18

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T00:25:04.460757Z digest=sha256:80259f041e527c2c8b0903f1b9148cdd99b036902be95d33d9066084cd9aa4e5

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

Resolution
metadata mismatch
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-09T19:34:51.433422Z digest=sha256:03aee3f35c3901e3d9f039bf14d7ec2a38959400693b60cd9c0bf6b2af33e028

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-19T21:49:07.440832Z digest=sha256:eeebcb484c3bac63a1a03dca83c50361ed02c5b94049319a43bfe82a154c7804

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T10:40:37.283129Z digest=sha256:7f1943bbf9feed8f3850b0c6af815fd6d1bacc5653fe2b2985cd199792a37302

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T03:53:38.554457Z digest=sha256:cacef81c75b8599ca6f92bd5a9aa078eb0782e10101c7f7877bc8f850b3cfd1c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T08:09:57.542558Z digest=sha256:c8f478164c4cf9f72c15404f350d2a16dccfe3c9a9f75da78598a89a4b58536a

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=sha256:469ea7e23f930fb12814f946ebf4b2c147b86c31e65b063364b8485435c7c748

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T11:13:36.521513Z digest=sha256:066a89560b6dcf4e6bedaa3fd10c02bbfcb821569f63fa4c49f50e689da367bb