𝗝𝗼𝘂𝗿𝗻𝗮𝗹 𝗡𝗮𝘁𝘂𝗿𝗮𝗹 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 - 𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗜𝘀𝘀𝘂𝗲 𝗼𝗻 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 𝗳𝗼𝗿 𝗟𝗼𝘄-𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀

URL - https://loreslm.github.io/specialissue
Neural language models have revolutionised natural language processing (NLP) and have provided state-of-the-art results for many tasks. However, their effectiveness is largely dependent on the pre-training resources. Therefore, language models (LMs) often struggle with low-resource languages in both training and evaluation. Recently, there has been a growing trend in developing and adopting LMs for low-resource languages. This special issue aims to provide a forum for researchers to share and discuss their ongoing work on LMs for low-resource languages.

𝗧𝗼𝗽𝗶𝗰𝘀
We invite submissions on a broad range of topics related to the development and evaluation of neural language models for low-resource languages, including but not limited to the following.

- Building language models for low-resource languages.
- Adapting/extending existing language models/large language models for low-resource languages.
- Corpora creation and curation technologies for training language models/large language models for low-resource languages.
- Benchmarks to evaluate language models/large language models in low-resource languages.
- Prompting/in-context learning strategies for low-resource languages with large language models.
- Review of available corpora to train/fine-tune language models/large language models for low-resource languages.
- Multilingual/cross-lingual language models/large language models for low-resource languages.
- Applications of language models/large language models for low-resource languages (i.e. machine translation, chatbots, content moderation, etc.

𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗗𝗮𝘁𝗲𝘀
Paper submission: December 31, 2025
First decision: March 31, 2026- April 30, 2026
Revised version submission: May 1, 2026- June 1, 2026
Final decision: August 30, 2026

𝗦𝘂𝗯𝗺𝗶𝘀𝘀𝗶𝗼𝗻
Submissions should be formatted according to the journal guidelines available - https://www.cambridge.org/core/journals/natural-language-processing/information/author-instructions/preparing-your-materials and submitted through the manuscript submission system https://mc.manuscriptcentral.com/nlp. To ensure your manuscript is considered for this special issue, please select “Language Models for Low-Resource Languages” under Special Issue Designation when uploading your manuscript.

𝗚𝘂𝗲𝘀𝘁 𝗘𝗱𝗶𝘁𝗼𝗿𝘀
Hansi Hettiarachchi, Lancaster University, UK
Tharindu Ranasinghe, Lancaster University, UK
Paul Rayson, Lancaster University, UK
Ruslan Mitkov, Lancaster University, UK
Mohamed Gaber, Queensland University of Technology, Australia

𝗚𝘂𝗲𝘀𝘁 𝗘𝗱𝗶𝘁𝗼𝗿𝗶𝗮𝗹 𝗕𝗼𝗮𝗿𝗱
Gábor Bella - IMT Atlantique, France
Ana-Maria Bucur - University of Bucharest, Romania
Çağrı Çöltekin - University of Tübingen, Germany
Vera Danilova - Uppsala University, Sweden
Ona de Gibert - University of Helsinki, Finland
Ignatius Ezeani - Lancaster University, UK
Amal Htait - Aston University, UK
Ali Hürriyetoğlu - Wageningen University & Research, Netherlands
Danka Jokic - University of Belgrade, Serbia
Diptesh Kanojia - University of Surrey, UK
Taro Watanabe - Nara Institute of Science and Technology, Japan
Muhidin Mohamed - Aston University, UK
Alistair Plum - University of Luxembourg, Luxembourg
Damith Premasiri - Lancaster University, UK
Guokan Shang - Mohamed bin Zayed University of Artificial Intelligence, France
Ravi Shekhar - University of Essex, UK