Four years ago, NLLB set a milestone with MT for 200 languages. Today we present OMT: a family of models that extend support to 1600 languages while delivering competitive results in high/mid-resource language, with our 1B-8B models matching frontier and open 70B LLMs.
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📢I'm organizing a BoF session at #EACL2026 called Tokenization & Beyond, aiming to gather researchers exploring tokenization and alternatives such as byte-level and pixel-based approaches. Sign up using the form if you're interested! #NLProc @eaclmeeting
New benchmark evaluates 🔎 #AI detection tools across languages, 🌍 finding performance gaps 📉 in low-resource languages and challenges ⚠️ with distinguishing AI-translated and hybrid human–AI text.
@jasonslucas1 @adaku_uchendu @penn_state @Visa