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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 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 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:12:26.108646Z

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 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.

source=pdf_text observed=2026-08-07T15:12:26.108646Z digest=sha256:dfd142ce97c7740f20ed6b505631783f10e2e1120e77a3d64e0dcf5b38b0e220

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.

source=arxiv_source observed=2026-08-07T14:33:51.619386Z digest=sha256:2f323b4560196623d7496bf76fd8b2319094a024dd10b84f8eb9e7d001ab2d9c

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.

source=arxiv_source observed=2026-08-06T15:13:15.625414Z digest=sha256:6849c6843deb53b48b0538ca97d40001b9130a8064bedd5cf2b2608bdc3b429d

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.

source=arxiv_source observed=2026-08-05T22:23:09.823900Z digest=sha256:c35fee176cfb9c57bfb1ff5811faf5d28c01d84dc718282f58ffe7fba421a8b3

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

source=pdf_text observed=2026-05-10T18:30:17.607269Z digest=sha256:b26ea53f70d26ccba43202ecd81fe77204749d2f8f1c69defdaf2308640be9d4

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

source=arxiv_source observed=2026-05-09T19:34:51.433422Z digest=sha256:b54f6bb8ce981c5d879a1e542791c30bee48647c8ac639c336822705849b0888