This is a Plain English Papers summary of a research paper called AI-Built Southeast Asian Image Dataset 50x Larger Than Previous Collections, Shows Web Crawling Beats Crowdsourcing. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Overview
- SEA-VL is an initiative to create culturally relevant vision-language data for Southeast Asia.
- Current AI models poorly represent Southeast Asian cultural nuances.
- Involves local contributors to ensure cultural authenticity.
- Compares crowdsourcing, web crawling, and image generation approaches.
- Collected 1.28 million culturally relevant images, 50x larger than existing datasets.
- Web crawling achieved ~85% cultural relevance, proving more efficient than crowdsourcing.
- AI-generated images failed to accurately represent Southeast Asian cultures.
Plain English Explanation
Southeast Asia is home to incredible cultural diversity, with hundreds of languages and distinct traditions. Yet when it comes to AI systems that combine vision and language, these cultures are largely invisible. The [SEA-VL project](https://aimodels.fyi/papers/arxiv/crowdsourc...
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