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Paper Citation Record · LEDGER

CBBQ: A Chinese Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2306.16244.

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

pith.paper-citation-record.v1
2306.16244 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 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:17:26.723290Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T09:24:14.014051Z

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 0c0b38fe-4593-4552-94dd-9939bdb963cb · inbound

Low-Resource Languages Jailbreak GPT-4 cites this paper.

Low-Resource Languages Jailbreak GPT-4 CBBQ: A Chinese Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-17T09:24:14.017094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-17T09:24:13.911401Z digest=sha256:6b6b67e1320a7bc09fe557d2f43c36719ec0a22b46577e91c8a82471946edc42

Observation 719252a1-2bff-4c05-aa12-071d48ef29e7 · 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 CBBQ: A Chinese Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T10:17:26.723290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:17:26.723290Z digest=sha256:6eb80e6cd94ec1860b9cbc6bfa5ec99a4f6303034940f43a043b977d8f4e4649

Observation b6ca40df-5202-4e74-9d4c-d7ccea68f00e · inbound

McBE: A Multi-task Chinese Bias Evaluation Benchmark for Large Language Models cites this paper.

McBE: A Multi-task Chinese Bias Evaluation Benchmark for Large Language Models CBBQ: A Chinese Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T20:43:51.221195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:43:51.221195Z digest=sha256:25e9563e4470494c6be0c8df72ab9614953324c872441c4173c27a03c42b5f77

Observation f3063778-4f64-47f3-a354-e37cb9365fdd · inbound

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages cites this paper.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages CBBQ: A Chinese Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-04T11:21:55.744048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:21:55.744048Z digest=sha256:75432165a491a93ceab98fbe602cfbb24af64c46c34812b3e909b13562d17920