Paper Citation Record · LEDGER

GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2312.06315.

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

pith.paper-citation-record.v1
2312.06315 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:14:19.816141Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T15:36:08.643164Z

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 92e0b988-bee8-46c4-9b69-be9666962c38 · inbound

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

Bias Unveiled: Investigating Social Bias in LLM-Generated Code GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T19:46:44.648128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31cad494-b29c-4f24-9c9b-93a6eab0001c · 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) GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T10:59:29.143116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0186f663-106e-4d56-b52e-bc8829b8046b · inbound

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs cites this paper.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:26.108646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cddf36f-b5ea-4616-aa22-1bbdfb430b70 · inbound

B-score: Detecting biases in large language models using response history cites this paper.

B-score: Detecting biases in large language models using response history GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:51.619386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbc1596f-dd9b-45ad-9750-fe327c3bb696 · inbound

Are Bias Evaluation Methods Biased ? cites this paper.

Are Bias Evaluation Methods Biased ? GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T19:14:19.816141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d80fc10-12bd-473b-a7d4-f90f8bf03b71 · inbound

Dutch CrowS-Pairs: Adapting a Challenge Dataset for Measuring Social Biases in Language Models for Dutch cites this paper.

Dutch CrowS-Pairs: Adapting a Challenge Dataset for Measuring Social Biases in Language Models for Dutch GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:15.625414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8975db38-d349-4b51-bca7-b0767daddc51 · inbound

BharatBBQ: A Multilingual Bias Benchmark for Question Answering in the Indian Context cites this paper.

BharatBBQ: A Multilingual Bias Benchmark for Question Answering in the Indian Context GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T22:23:09.823900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b5c5e03-35c9-46d6-aefd-3d2ab3171395 · inbound

ViDA-UGC: Detailed Image Quality Analysis via Visual Distortion Assessment for UGC Images cites this paper.

ViDA-UGC: Detailed Image Quality Analysis via Visual Distortion Assessment for UGC Images GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T17:27:53.100549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6332d89-bc9f-40d1-a1d2-81d7bceab443 · inbound

Poison Once, Refuse Forever: Weaponizing Alignment for Injecting Bias in LLMs cites this paper.

Poison Once, Refuse Forever: Weaponizing Alignment for Injecting Bias in LLMs GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-15T16:51:54.980320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c05908f-f402-4895-b99b-721b0a7f0041 · 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 GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:30:51.220617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c9ade6bf-b53f-4231-b2d6-6ac7f1a14409 · inbound

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

Social Bias in LLM-Generated Code: Benchmark and Mitigation GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 148

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:36:08.646346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.