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Paper Citation Record · LEDGER

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

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 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 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:44:34.503503Z

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
  • parse uncertain0
  • 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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T22:30:44.520703Z digest=sha256:55935b1f1fe28f8dc95de13ac7e5201274e4393948749436afed2a3b6efb8c4d

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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T04:13:05.328492Z digest=sha256:9a456baac4a6099df56eab0796446e63241e5cbc735b0d727b6335a616196499

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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T23:07:23.738519Z digest=sha256:218492f7ba517e41db079840f3401962d251a64a143ea2aaa2121e527691fcf1

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=sha256:90f8cccf2b846a54f149fda41904d9c139325521e908e1ee774e3cc83e978cba

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:e951528914366423b4656cac71dfd381eff034778e3cad94ca4846d1c1482923

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T18:30:17.607269Z digest=sha256:9f95534f862e51fd54365c53fafdce1cdf352f27d2f4241df4ff141dc6e5662e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T17:27:13.339411Z digest=sha256:71429f2ae766b83b862d8d8b189fdfc634a34583d6dce3f28f58dc85a0af9f28

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T06:42:54.471013Z digest=sha256:8cde2310a563aeef6a70fd9e414e026cdac440b61e17957c7ff5f8e78ffac580

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T18:46:11.998827Z digest=sha256:0b5a5fd4b29a642ffc1b28a39e204d52724b8cd1f431841320043ae1aad96ae5

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-26T09:12:19.873337Z digest=sha256:e07f0a7773bf5d2e55b5ac6b02f877050409be21a90d86a6819b2dd655885e46

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-29T02:42:12.026696Z digest=sha256:8758984e8ee4c803ca4ec7d3bd4eb7aa99067edb5e1fbb94ac696d1280f0b6d0

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:cb08a02f115514f293a828a3b8371ab2e0a61e350783ff06c833af93c2d225e0