Paper Citation Record · LEDGER

Towards Auditing Large Language Models: Improving Text-based Stereotype Detection

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2311.14126.

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

pith.paper-citation-record.v1
2311.14126 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:56:29.929671Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T07:22:28.949334Z

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 7dfe604c-d1e4-4e6f-8dac-f54b617b2dce · inbound

LangFair: A Python Package for Assessing Bias and Fairness in Large Language Model Use Cases cites this paper.

LangFair: A Python Package for Assessing Bias and Fairness in Large Language Model Use Cases Towards Auditing Large Language Models: Improving Text-based Stereotype Detection

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:29.929671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d544d047-0b67-4cfb-8265-91f012238fb0 · inbound

Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applications cites this paper.

Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applications Towards Auditing Large Language Models: Improving Text-based Stereotype Detection

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-09T17:43:55.843374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eac7c565-51b5-4df9-88cc-6754703ce88d · inbound

StereoTales: A Multilingual Framework for Open-Ended Stereotype Discovery in LLMs cites this paper.

StereoTales: A Multilingual Framework for Open-Ended Stereotype Discovery in LLMs Towards Auditing Large Language Models: Improving Text-based Stereotype Detection

Reference 117

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:51:27.215251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation af7fbf30-876a-4fcd-9aaa-3e8befaa712e · inbound

StereoTales: A Multilingual Framework for Open-Ended Stereotype Discovery in LLMs cites this paper.

StereoTales: A Multilingual Framework for Open-Ended Stereotype Discovery in LLMs Towards Auditing Large Language Models: Improving Text-based Stereotype Detection

Reference 117

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:22:28.952117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.