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New ALTO dataset targets tech-facilitated gender-based violence in Arabic, French, Swahili

By PulseAugur Editorial · [1 sources] ·

Researchers have developed the ALTO dataset, a new collection of 3,022 instances of tech-facilitated gender-based violence (TFGBV) in Levantine Arabic, African French, and Swahili. This community-led effort, in collaboration with civil society organizations from Jordan, Francophone West Africa, and Kenya, addresses the lack of culturally and linguistically relevant data for TFGBV detection in non-Global North languages. Benchmarking experiments revealed that existing harmful content detection models perform poorly on this dataset, particularly missing covert harms and showing higher error rates in Swahili, though fine-tuning shows improvement. AI

IMPACT This dataset aims to improve AI's ability to detect and combat online gender-based violence in underrepresented languages and cultural contexts.

RANK_REASON The cluster is about a new academic dataset and paper released on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New ALTO dataset targets tech-facilitated gender-based violence in Arabic, French, Swahili

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The cluster is about a new academic dataset and paper released on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Tianwei Zhang, Ivy Njoki Nyagwencha, Zahraa Dirani, Shalini Joshi, Scott A. Hale ·

    ALTO: African and Levantine Tech-Facilitated Gender-Based Violence Corpus

    arXiv:2611.06706v1 Announce Type: cross Abstract: Tech-facilitated gender based violence (TFGBV) is a pervasive online harm affecting women and gender minority groups through its many direct and covert forms. Current models and annotated datasets for gendered harm detection are d…

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