Measuring research progress and linguistic inclusion in low-resource languages; analysis of 1,158 open-access NLP papers from 2020–2025 reveals attention and representation gaps
Read the original at arxiv.org→arXiv:2610.30296v1 Announce Type: new Abstract: Large Language Models (LLMs) have accelerated research on low-resource and multilingual NLP, but their effectiveness in creating an equitable landscape remains...
Original headline: "Measuring Research Progress and Linguistic Inclusion in Low-Resource Languages"
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- Oct 23, 04:00 UTC arXiv cs.CL lead source Measuring Research Progress and Linguistic Inclusion in Low-Resource Languages