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Paper Citation Record · LEDGER

Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2304.03738.

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

pith.paper-citation-record.v1
2304.03738 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 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 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:40:40.995887Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:59:45.831622Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation efe7d589-3650-42ba-a9c9-59b8685deab7 · inbound

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment cites this paper.

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 220

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:30:45.069388Z

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=2026-05-17T22:30:44.520703Z digest=sha256:c02d34f20c045bb80514041e144fca3042483436ef68155bc5c68b5f55bc23d1

Observation 40ea4001-3005-4b34-85bd-bc55fda8c160 · inbound

Data-Centric Foundation Models in Computational Healthcare: A Survey cites this paper.

Data-Centric Foundation Models in Computational Healthcare: A Survey Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 84

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verified exact
arxiv_id, observed 2026-05-24T04:13:53.075638Z

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=2026-05-24T04:13:05.328492Z digest=sha256:0b14aaf52fa57564d4e452ad33732c86f5d0ed18c2b63a977c149c367765caaf

Observation a12c259d-dd46-45da-bcc1-07d6eb473593 · inbound

Social and Ethical Risks Posed by General-Purpose LLMs for Settling Newcomers in Canada cites this paper.

Social and Ethical Risks Posed by General-Purpose LLMs for Settling Newcomers in Canada Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 30

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verified exact
arxiv_id, observed 2026-05-23T23:08:35.448009Z

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=2026-05-23T23:07:23.738519Z digest=sha256:75a0a92cadeba42a209c373c08708a6226cca1f2be3482348733b61932f98667

Observation c6917448-6c05-4d4f-8a6c-02ff1c01ef1e · inbound

Understanding Design Fixation in Generative AI cites this paper.

Understanding Design Fixation in Generative AI Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 22

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unresolved
no resolver link, observed 2026-08-08T17:40:40.995887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:40:40.995887Z digest=sha256:f142635341b7c324783813019da2a3d91189d65430463729eacef9e8969a55e7

Observation 47abcf14-5598-461a-91cf-003ed3205f83 · inbound

Unbiased Evaluation of Large Language Models from a Causal Perspective cites this paper.

Unbiased Evaluation of Large Language Models from a Causal Perspective Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-08T14:51:15.389935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T14:51:15.389935Z digest=sha256:9a7987583e76cbddbe0ad4e0d8d5ac73334ecab49416dedaf0028249fbe41953

Observation 1706ab68-c170-4a73-84d1-62f96ce29302 · inbound

Large language models perpetuate bias in palliative care: development and analysis of the Palliative Care Adversarial Dataset (PCAD) cites this paper.

Large language models perpetuate bias in palliative care: development and analysis of the Palliative Care Adversarial Dataset (PCAD) Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-08T10:59:29.146298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:59:29.146298Z digest=sha256:ce7f4967ca9344c9e83046c38d73a73582a9fe4c70011bc1d95c4c9f1c4c2fa2

Observation 341d14a3-bd85-4e36-9082-aa967d100ff4 · inbound

The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs cites this paper.

The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 117

Resolution
unresolved
no resolver link, observed 2026-08-07T10:17:26.952493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:17:26.952493Z digest=sha256:ff43cfb7e65f3ca8bae21d671fcb21ecfaae7c1df20152f9bbdd53e381cca7e1

Observation 6434a33d-4e04-41d0-b673-d3fd8b4ea65f · inbound

The Potential Impact of Disruptive AI Innovations on U.S. Occupations cites this paper.

The Potential Impact of Disruptive AI Innovations on U.S. Occupations Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T17:13:43.619605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:43.619605Z digest=sha256:06a08d963e0f36323a1066b140fa24d7752a251869a4c4b98f5dee2f5c50e56a

Observation bc02a5e6-873b-464e-bc47-27d0e7a17e36 · inbound

Identifying Pre-training Data in LLMs: A Neuron Activation-Based Detection Framework cites this paper.

Identifying Pre-training Data in LLMs: A Neuron Activation-Based Detection Framework Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T15:15:18.466696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:15:18.466696Z digest=sha256:908745ae624961f09e1927c32f6b614791262bd396de6e46714fb8cebe6126bf

Observation 90de9e0c-c90b-4408-9bff-7ab20ad5717d · inbound

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation cites this paper.

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-03T03:04:43.552922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:04:43.552922Z digest=sha256:a4a7bf96d483a63076677db2927bab244ccaebf5ec1dfcb9420a96fd85d5da0d

Observation 1b1c7f38-a1bc-4ffb-b739-772316743b4d · inbound

Can We Trust a Black-box LLM? LLM Untrustworthy Boundary Detection via Bias-Diffusion and Multi-Agent Reinforcement Learning cites this paper.

Can We Trust a Black-box LLM? LLM Untrustworthy Boundary Detection via Bias-Diffusion and Multi-Agent Reinforcement Learning Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:30:51.278291Z

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=2026-05-10T18:30:17.607269Z digest=sha256:8cb4a4a74edcf0b84bb012ed4caa57f6e413080e0839e7a165149c7dd25253ee

Observation 90b09e2b-ae38-4a88-ac4d-989f5d067c34 · inbound

Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs cites this paper.

Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:46:39.068365Z

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=2026-05-10T17:27:13.339411Z digest=sha256:2c063848d528428f4b0644f080c3c07e071d56b32513d76f453914ae43764d81

Observation fda17a79-52f1-454c-adc1-fec364a4659c · inbound

Beyond Static Benchmarks: Synthesizing Harmful Content via Persona-based Simulation for Robust Evaluation cites this paper.

Beyond Static Benchmarks: Synthesizing Harmful Content via Persona-based Simulation for Robust Evaluation Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T06:46:37.344226Z

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=2026-05-10T06:42:54.471013Z digest=sha256:f594a79252724145feeac436da0c96fa39848d6614b1fb1e27290b2c290ef6a4

Observation 90f77d0e-5515-4bd1-9de4-49b356eee835 · inbound

LOKI: Memory-Free Null-Space Constrained Lifelong Knowledge Editing cites this paper.

LOKI: Memory-Free Null-Space Constrained Lifelong Knowledge Editing Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-04T02:59:25.204203Z

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=2026-06-26T18:46:11.998827Z digest=sha256:5f0ee3ecd1e3b92d76ab19727636d8bb2784fc915ae76a403e6087e7ac602ce6

Observation 3752411c-e8ef-4243-abbd-d3f0629a1e20 · inbound

Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasets cites this paper.

Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasets Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 147

Resolution
verified exact
arxiv_id, observed 2026-07-04T09:59:45.833090Z

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=2026-06-26T09:12:19.873337Z digest=sha256:d851d55e953d62aff65f241a48f075bbc747e64e4af88be08688441e8e225f58

Observation c771c12c-2ec2-4ac2-b4da-8aa12fea8be6 · inbound

An LLM-Powered Semantic Alignment Framework for Journal Recommendation cites this paper.

An LLM-Powered Semantic Alignment Framework for Journal Recommendation Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 98

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T18:05:58.495963Z

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=2026-06-29T02:42:12.026696Z digest=sha256:84882bae2d6446ef5131cd1745cb707e1c5d7229c4db3fb5d1c685dce3202009

Observation 15f074f6-1ad5-452b-af55-9103cc4219d2 · inbound

What Current AI Benchmarks Leave Unmeasured: Modality, Search, Citations, and Implications (for Safety Evaluations) cites this paper.

What Current AI Benchmarks Leave Unmeasured: Modality, Search, Citations, and Implications (for Safety Evaluations) Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:34.503503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:34.503503Z digest=sha256:edbeb192d3919387328d7a2172e8e024409bddd0bd9da6552321e76d842461f3