Measuring Research Progress and Linguistic Inclusion in Low-Resource Languages
Title: Measuring Research Progress and Linguistic Inclusion in Low-Resource Languages
标题：衡量低资源语言的研究进展与语言包容性
Computer Science > Computation and Language arXiv:2610.30296 (cs) [Submitted on 21 Oct 2026] Title: Measuring Research Progress and Linguistic Inclusion in Low-Resource Languages Authors: Atnafu Lambebo Tonja, Tadesse Destaw Belay, Jesujoba Oluwadara Alabi, Israel Abebe Azime, Benjamin Rosman, Ehsan Shareghi, Thamar Solorio, Pontus Stenetorp, Monojit Choudhury.
计算机科学 > 计算与语言 arXiv:2610.30296 (cs) [2026年10月21日提交] 标题：衡量低资源语言的研究进展与语言包容性 作者：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.
摘要：大型语言模型（LLMs）加速了低资源和多语言自然语言处理（NLP）的研究，但它们在创造公平环境方面的有效性仍未得到充分评估。我们分析了2020年至2025年间发表的1,158篇同行评审开放获取论文，考察了对低资源语言（LRLs）的研究关注度以及在不同语言和说话者群体中的代表性。
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.
为了评估超越出版数量的语言包容性，我们引入了语言包容性框架（LIF），这是一个多维框架，从研究增长、代表性扩展、代表性连续性和分布公平性四个维度衡量语言包容性。虽然年度出版物从52篇增加到415篇，在ACL文集中的出版份额增长了5.4倍，但这种增长主要集中在已有代表性的语言上，而非扩大对代表性不足语言的覆盖范围。
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.
进一步分析显示，在我们分析的低资源语言中，亚洲语言的使用者占总数的64.1%，但仅获得46.7%的语言代表性份额（为其比例份额的0.7倍），而欧洲语言则获得了其比例份额的5.3倍。在国家层面，撒哈拉以南非洲和东南亚等语言多样性丰富的地区显示出最低的语言覆盖率。
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.
在大陆层面应用该框架后，我们发现没有一个地区在所有四个维度上都表现良好，这表明仅靠研究增长并不能作为衡量迈向公平和包容性语言技术进展的可靠指标。