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JNLP-LMLRL 2026 : LNLP - ๐ฆ๐ฝ๐ฒ๐ฐ๐ถ๐ฎ๐น ๐๐๐๐๐ฒ ๐ผ๐ป ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐ ๐ผ๐ฑ๐ฒ๐น๐ ๐ณ๐ผ๐ฟ ๐๐ผ๐-๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ ๐๐ฎ๐ป๐ด | |||||||||||||
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๐๐ผ๐๐ฟ๐ป๐ฎ๐น ๐ก๐ฎ๐๐๐ฟ๐ฎ๐น ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐ฃ๐ฟ๐ผ๐ฐ๐ฒ๐๐๐ถ๐ป๐ด - ๐ฆ๐ฝ๐ฒ๐ฐ๐ถ๐ฎ๐น ๐๐๐๐๐ฒ ๐ผ๐ป ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐ ๐ผ๐ฑ๐ฒ๐น๐ ๐ณ๐ผ๐ฟ ๐๐ผ๐-๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ๐
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. ๐ง๐ผ๐ฝ๐ถ๐ฐ๐ 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.) ๐๐บ๐ฝ๐ผ๐ฟ๐๐ฎ๐ป๐ ๐๐ฎ๐๐ฒ๐ 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 ๐ฆ๐๐ฏ๐บ๐ถ๐๐๐ถ๐ผ๐ป 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 โLanguage Models for Low-Resource Languagesโ 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 Gรกbor Bella - IMT Atlantique, France Ana-Maria Bucur - University of Bucharest, Romania รaฤrฤฑ รรถltekin - University of Tรผbingen, Germany Vera Danilova - Uppsala University, Sweden Ona de Gibert - University of Helsinki, Finland Ignatius Ezeani - Lancaster University, UK Amal Htait - Aston University, UK Ali Hรผrriyetoฤlu - 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 |
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