BYOL: Bring Your Own Language into LLMs
A scalable framework for bringing low‑resource and extreme‑low‑resource languages into modern LLMs. Demonstrated significant accuracy gains for Chichewa, Māori, and Inuktitut through tailored LLM pathways.
Impact
Demonstrated significant accuracy gains for Chichewa, Māori, and Inuktitut through tailored LLM pathways.
Ethics & Responsibility
Addresses global language inequity by expanding AI access while preserving multilingual and cultural integrity.
Project Details
BYOL introduces a unified framework for integrating any language—especially low‑resource and extreme‑low‑resource languages—into large language models. It classifies languages by digital resource availability and applies tailored pathways, from data refinement and synthetic text generation to translation‑mediated inclusion. Applied to languages such as Chichewa, Māori, and Inuktitut, BYOL delivers measurable performance improvements while maintaining broader multilingual capabilities. The project also releases new human‑translated benchmark datasets and open‑source tools to support inclusive AI development.
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