3 papers
cs.CL2026
Calibrating Beyond English: Language Diversity for Better Quantized Multilingual LLM
Everlyn Asiko Chimoto, Mostafa Elhoushi, Bruce A. Bassett
Quantization is an effective technique for reducing the storage footprint and computational costs of Large Language Models (LLMs), but it often results in performance degradation.…
cs.CL2025
The Esethu Framework: Reimagining Sustainable Dataset Governance and Curation for Low-Resource Languages
Jenalea Rajab, Anuoluwapo Aremu, Everlyn Asiko Chimoto +12
This paper presents the Esethu Framework, a sustainable data curation framework specifically designed to empower local communities and ensure equitable benefit-sharing from their l…
cs.CL2025
GrammaMT: Improving Machine Translation with Grammar-Informed In-Context Learning
Rita Ramos, Everlyn Asiko Chimoto, Maartje ter Hoeve +1
We introduce GrammaMT, a grammatically-aware prompting approach for machine translation that uses Interlinear Glossed Text (IGT), a common form of linguistic description providing…