Overview
This editorial highlights a significant opportunity for researchers in the field of natural language processing (NLP) to contribute to a special issue focused on language models tailored for low-resource languages. The issue aims to foster discussion and dissemination of innovative approaches in developing and evaluating these models, which are crucial for enhancing linguistic diversity in AI applications.
Background & Relevance
The advent of neural language models has transformed the landscape of NLP, achieving remarkable performance across various tasks. However, the dependency on extensive pre-training resources poses challenges for languages with limited data. This special issue addresses the urgent need for research that focuses on low-resource languages, ensuring that advancements in NLP are inclusive and beneficial for a broader range of linguistic communities.
Key Details
- Paper Submission Deadline: December 31, 2025
- First Decision Period: March 31, 2026 – April 30, 2026
- Revised Version Submission: May 1, 2026 – June 1, 2026
- Final Decision Date: August 30, 2026
- Submission Guidelines: Follow the journal’s formatting instructions available at Natural Language Processing Author Instructions
- Submission Portal: Manuscripts should be submitted via Manuscript Central and select “Language Models for Low-Resource Languages” under Special Issue Designation.
Eligibility & Participation
This call for papers is open to researchers and practitioners working on language models for low-resource languages. It targets individuals and teams engaged in developing methodologies, creating datasets, or applying language models in practical scenarios.
Submission or Application Guidelines
To participate, authors should prepare their manuscripts in accordance with the journal’s guidelines. Submissions must be made through the designated portal, ensuring that the special issue designation is selected to facilitate proper review.
Additional Context / Real-World Relevance
The focus on low-resource languages is vital for promoting linguistic equity in AI technologies. By advancing research in this area, the NLP community can contribute to the preservation of diverse languages and cultures, enabling applications such as machine translation, chatbots, and more to serve a wider audience. This initiative aligns with ongoing efforts to enhance the inclusivity and accessibility of AI solutions.
Conclusion
Researchers are encouraged to explore this opportunity to contribute to the evolving field of NLP. By submitting their work on language models for low-resource languages, they can play a crucial role in shaping a more inclusive future for language technology. Interested parties should prepare their submissions in line with the outlined guidelines and deadlines.
Category: CFP & Deadlines
Tags: nlp, language-models, low-resource-languages, neural-networks, machine-translation, corpora, multilingual, cross-lingual, deep-learning
