Research growth does not ensure fair inclusion of low-resource languages
Measuring Research Progress and Linguistic Inclusion in Low-Resource Languages
Computation and Language
Summary
Many low-resource languages, spoken by millions, receive little attention in language technology research. The authors studied over 1,100 papers to see how research on these languages is growing and who benefits. They created a framework that shows although research has increased overall, it mostly focuses on well-represented languages, leaving many less spoken and diverse languages behind. This means progress in language technology is not equally shared across different regions and language groups.
What this means in practice
- •For language technology developers: Prioritize truly underserved low-resource languages when allocating research and development efforts for more balanced language technology coverage.
- •For technology policy teams: Use the Linguistic Inclusion Framework to measure and guide equitable investment in language technology projects across diverse global regions.
Authors
Atnafu Lambebo Tonja, Tadesse Destaw Belay, Jesujoba Oluwadara Alabi, Israel Abebe Azime, Benjamin Rosman, Ehsan Shareghi, Thamar Solorio, Pontus Stenetorp, Monojit Choudhury
Abstract
Large Language Models (LLMs) have accelerated research on low-resource and multilingual NLP, but their effectiveness in creating an equitable landscape remains unmapped. We analyze 1,158 peer-reviewed open-access papers published between 2020 and 2025, examining research attention to low-resource languages (LRLs) and representation across language and speaker populations. To assess linguistic inclusion beyond publication counts, we introduce the Linguistic Inclusion Framework (LIF), a multidimensional framework that measures linguistic inclusion in four dimensions: research growth, representation expansion, representation continuity, and distributional equity. While annual publications grew from 52 to 415, a 5.4X increase in their ACL Anthology publication share, this growth largely concentrated on represented languages rather than expanding coverage of underrepresented languages. Further analysis shows that languages spoken in Asia account for 64.1% of speakers across LRLs we analyze but receive only 46.7% of the language representation share (0.7X their proportional share), while European languages receive 5.3X their proportional share. At the country level, linguistically diverse regions such as sub-Saharan Africa and Southeast Asia show the lowest language coverage ratios. Applying the framework at the continental level, we find that no region scores well on all four dimensions, showing that research growth alone is not a reliable metric of progress toward equitable and inclusive language technology\footnote{We will release all collected and annotated data for research purposes}.