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New benchmark measures stereotypical bias in Goan identity groups

Researchers have introduced AmchiBias, a novel benchmark designed to measure stereotypical bias within Goan identity groups, utilizing a dataset of minimal pairs in both English and Konkani. The benchmark evaluates five multilingual encoder models, revealing that while models show high bias for pan-Indian groups when queried in English, their performance in Konkani is near chance, indicating a lack of linguistic and cultural competence for hyperlocal identities. This work highlights a significant gap in low-resource multilingual NLP evaluation for specific community identities. AI

IMPACT Highlights a critical gap in low-resource multilingual NLP evaluation for hyperlocal community identities.

RANK_REASON Academic paper published on arXiv detailing a new benchmark for NLP bias. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Michelle Barbosa, Sebastian Pad\'o, Franziska Weeber ·

    AmchiBias: Measuring Stereotypical Bias in Goan Identity Groups with a Minimal Pair Dataset in English and Konkani

    arXiv:2606.15191v1 Announce Type: new Abstract: Socio-cultural stereotypical bias is an important consideration in the development and deployment of NLP systems. It is however often considered only at the national level, despite rich subnational socio-cultural structures. We pres…