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    <abstract>While large language models (LLMs) have substantially expanded support for non-English languages, their ability to generalize across typologically diverse languages and produce contextually appropriate, culturally grounded responses remains a significant challenge. This tutorial examines the rapidly evolving area of understanding, evaluating, and improving the multilingual capabilities and multicultural alignment of LLMs. We will primarily focus on cutting-edge advances and latest publications from 2025–2026, while incorporating selected introductory material to provide necessary background and to ensure accessibility for a broad audience. Participants will gain an up-to-date view of both methods and practical insights, including multilingual pre-, mid- and post-training, multilingual-specific optimization techniques, culturally aware evaluation, and key open problems in developing more fair, inclusive, and robust LLMs.</abstract>
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%0 Conference Proceedings
%T Multilingual and Multicultural LLMs
%A Xu, Wei
%A Adelani, David Ifeoluwa
%A Prabhakaran, Vinodkumar
%A Hooker, Sara
%A Ritter, Alan
%Y Marasović, Ana
%Y Glavaš, Goran
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-463-7
%F xu-etal-2026-multilingual
%X While large language models (LLMs) have substantially expanded support for non-English languages, their ability to generalize across typologically diverse languages and produce contextually appropriate, culturally grounded responses remains a significant challenge. This tutorial examines the rapidly evolving area of understanding, evaluating, and improving the multilingual capabilities and multicultural alignment of LLMs. We will primarily focus on cutting-edge advances and latest publications from 2025–2026, while incorporating selected introductory material to provide necessary background and to ensure accessibility for a broad audience. Participants will gain an up-to-date view of both methods and practical insights, including multilingual pre-, mid- and post-training, multilingual-specific optimization techniques, culturally aware evaluation, and key open problems in developing more fair, inclusive, and robust LLMs.
%U https://aclanthology.org/2026.emnlp-tutorials.6/
%P 10-11

Markdown (Informal)

[Multilingual and Multicultural LLMs](https://aclanthology.org/2026.emnlp-tutorials.6/) (Xu et al., EMNLP 2026)

• Multilingual and Multicultural LLMs (Xu et al., EMNLP 2026)

ACL

• Wei Xu, David Ifeoluwa Adelani, Vinodkumar Prabhakaran, Sara Hooker, and Alan Ritter. 2026. Multilingual and Multicultural LLMs. In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts, pages 10–11, Budapest, Hungary. Association for Computational Linguistics.