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Paper Citation Record · LEDGER

Quite Good, but Not Enough: Nationality Bias in Large Language Models -- A Case Study of ChatGPT

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.06996.

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

pith.paper-citation-record.v1
2405.06996 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:22:07.683889Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T00:00:47.854646Z

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 54d70642-5baf-4fb7-bd3f-4a413d6b5af2 · inbound

OrgAccess: A Benchmark for Role Based Access Control in Organization Scale LLMs cites this paper.

OrgAccess: A Benchmark for Role Based Access Control in Organization Scale LLMs Quite Good, but Not Enough: Nationality Bias in Large Language Models -- A Case Study of ChatGPT

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:22:07.683889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:22:07.683889Z digest=sha256:51b3da9910976b2bc0a11e5ea6af35cf24cf330d76be2e72be34e3cd7e18e39f

Observation ae83c5c0-b089-430a-9f37-cc238bdc5c63 · inbound

Measuring Stereotype and Deviation Biases in Large Language Models cites this paper.

Measuring Stereotype and Deviation Biases in Large Language Models Quite Good, but Not Enough: Nationality Bias in Large Language Models -- A Case Study of ChatGPT

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-22T00:00:47.856198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T23:57:16.883657Z digest=sha256:2f8bc461a6d194995a987e4380c7f621e1f4803702da6d797f02cb39a22f9fc1