Metraipolis › archive › dc_dedea8fc13ed

WikiOriginQA: Automated Construction of a QA Dataset with Knowledge Origins for Analyzing Cultural Bias — arXiv:2610.30677

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.30677
License (as archived): CC0-1.0
Archived: 2026-10-23T15:20:28.107Z
SHA-256 of the archived text: cacc12125942bc2236599ae9b92f2e77a5b78d7ca74718566f89b7bc77e34602
Stable URL of this page: https://metraipolis.com/documento/dc_dedea8fc13ed

How to cite

WikiOriginQA: Automated Construction of a QA Dataset with Knowledge Origins for Analyzing Cultural Bias — arXiv:2610.30677 — arXiv (en), https://arxiv.org/abs/2610.30677 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_dedea8fc13ed (Metraipolis archive dc_dedea8fc13ed, sha256 cacc12125942bc2236599ae9b92f2e77a5b78d7ca74718566f89b7bc77e34602)

BibTeX

@misc{dcdedea8fc13ed,
  title = {WikiOriginQA: Automated Construction of a QA Dataset with Knowledge Origins for Analyzing Cultural Bias — arXiv:2610.30677},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.30677},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_dedea8fc13ed; sha256 cacc12125942bc2236599ae9b92f2e77a5b78d7ca74718566f89b7bc77e34602},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.30677. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Existing datasets on cultural knowledge have been typically created by human annotators familiar with each culture. However, the process requires considerable human effort, presenting a significant challenge to scalability. To address this challenge, we introduce WikiOriginQA, a QA dataset automatically constructed by objectively representing the origins of knowledge through the creation dates of different Wikipedia language editions. Experimental results with the created dataset confirm that LLM performance tends to be biased toward Anglophone cultures. Furthermore, the results suggest the importance of knowledge propagation into the Anglosphere. These findings demonstrate the validity of our automated approach, enabling cultural bias evaluations with superior scalability across diverse languages without extensive manual annotation.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.CL, nuovi lavori del giorno).
Categorie arXiv: Computation and Language (cs.CL).
Pagina del lavoro: https://arxiv.org/abs/2610.30677 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-23T15:09:38.323Z dalla pagina https://arxiv.org/list/cs.CL/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).