Toward Culturally Grounded Natural Language Processing

ArXi:2603.26013v1 Announce Type: new Recent progress in multilingual NLP is often taken as evidence of broader global inclusivity, but a growing literature shows that multilingual capability and cultural competence come apart. This paper synthesizes over 50 papers from 2020--2026 spanning multilingual performance inequality, cross-lingual transfer, culture-aware evaluation, cultural alignment, multimodal local-knowledge modeling, benchmark design critiques, and community-grounded data practices. Across this literature.