{"id":995568,"date":"2024-01-05T08:06:54","date_gmt":"2024-01-05T16:06:54","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&p=995568"},"modified":"2025-03-31T11:56:28","modified_gmt":"2025-03-31T18:56:28","slug":"afmr-multicultural-analysis-and-empowerment","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/afmr-multicultural-analysis-and-empowerment\/","title":{"rendered":"AFMR: Multicultural Analysis and Empowerment"},"content":{"rendered":"
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Multicultural Analysis and Empowerment<\/h1>\n\n\n\n

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Academic research plays such an important role in advancing science, technology, culture, and society. This grant program helps ensure this community has access to the latest and leading AI models.<\/em><\/strong><\/p>\nBrad Smith, Vice Chair and President<\/cite><\/blockquote>\n\n\n\n

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AFMR Goal: Improve human interactions via sociotechnical research<\/h2>\n\n\n\n

which increases trust, human ingenuity, creativity, and productivity, and decreases the digital divide while reducing the risks of developing AI which does not benefit individuals and society<\/p>\n<\/div>\n\n\n\n

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The research projects primarily focus on enhancing language models, emphasizing underrepresented languages and cultures. Projects aim to improve the accuracy of health-related responses and fine-tune models for specific languages like Vietnamese and various Indian languages. Cultural intelligence is a key goal, promoting linguistic inclusivity and understanding model behavior with knowledge graph tools. Additional efforts involve developing model-editing techniques for interpretability and robustness, particularly in underrepresented languages. The overarching aim is to enhance language models for improved accuracy, adaptability, and inclusivity across diverse languages and cultures.<\/p>\n\n\n\n

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University of Pretoria<\/strong>: Vukosi Marivate (PI)<\/p>\n\n\n\n

The goal of this study is to extend the capabilities of foundation models [6] for ESL-speaking African communities by enhancing their ability to understand and generate content that accurately reflects the continent\u2019s socio-cultural specifics. This involves adapting models to users\u2019 specific needs, and linguistic styles; making the models more accessible and equitable for underrepresented groups. Through localized tuning and feedback, the project seeks to reduce performance gaps and tailor foundation models for diverse uses such as in legal, finance, and agriculture in Africa. The overarching goal is to provide users with the agency to customize foundation (language) models to their unique situations. <\/p>\n\n\n\n\n\n

University of Waterloo<\/strong>: Jimmy Lin (PI)<\/p>\n\n\n\n

The proposal aims to build robust foundation models for African languages to bridge the technology gap affecting these communities. The project objectives include design and optimization of model architecture, multilingual transfer learning, evaluation, and making the resources openly available.<\/p>\n\n\n\n

Related papers:<\/strong><\/p>\n\n\n\n