International Conference
'LAnguage TEchnologies for Low-resource Languages' (LaTeLL '2026)
Fes, Morocco
30 September, 1 and 2 October 2026
www.latell.org/2026/ [1]
Second Call for Papers
The conference
Natural Language Processing (NLP) has witnessed remarkable progress in recent years, largely driven by the emergence of deep learning architectures and, more recently, large language models (LLMs). Nevertheless, these advances have disproportionately benefited high-resource languages that possess abundant data for model training. By contrast, low-resource languages which account for at least 85% of the world's linguistic diversity and are often spoken by smaller or marginalised communities, have not yet reaped the full benefits of contemporary NLP technologies.
This imbalance can be attributed to several interrelated factors, including the scarcity of high-quality training data, limited computational and financial resources, and insufficient community engagement in data collection and model development. Developing NLP applications for low-resource languages poses major challenges, particularly the need for large, well-annotated datasets, standardised tools, and robust linguistic resources.
Although several workshops have previously addressed NLP for low-resource languages, _LaTeLL_ represents the first international conference dedicated specifically to the automatic processing of such languages. The event aims to provide a forum for researchers to present and discuss their latest work in NLP in general, and in the development and evaluation of language models for low-resource languages in particular.
Conference topics
We invite submissions on a broad range of themes concerning linguistic and computational studies focusing on low-resource languages, including but not limited to the following topics:
Language resources for low-resource languages
* Dataset creation and annotation * Evaluation methodologies and benchmarks for low-resource settings * Lexical resources, corpora, and linguistic databases * Crowdsourcing and community-driven data collection * Tools and frameworks for low-resource language processing
Core language technologies for low-resource languages
* Language modelling and pre-training for low-resource languages * Speech recognition, text-to-speech, and spoken language understanding * Phonology, morphology, word segmentation, and tokenisation * Syntax: tagging, chunking, and parsing * Semantics: lexical and sentence-level representation
NLP Applications for low-resource languages
* Information extraction and named entity recognition * Question answering systems * Dialogue and interactive systems * Summarisation * Machine translation * Sentiment analysis, stylistic analysis, and argument mining * Content moderation * Information retrieval and text mining
Multimodality and Grounding for low-resource languages
* Vision and language for low-resource contexts * Speech and text multimodal systems * Low-resource sign language processing
Ethics, Equity, and Social Impact for low-resource languages
* Bias and fairness in low-resource language technologies * Sociolinguistic considerations in technology development * Cultural appropriateness and sensitivity
Human-Centred Approaches in low-resource languages
* Usability and accessibility of low-resource language technologies * Educational applications and language learning * Community needs assessment and technology adoption * User experience research in low-resource contexts
Multilinguality and Cross-Lingual Methods for low-resource languages
* Multilingual language models and their adaptation * Code-switching and code-mixing * Cross-lingual transfer learning in low-resource languages.
Special Theme Track 1 -- Building Applications Based on Large Language Models for Low-Resource Languages
_LaTeLL'2026_ will feature a Special Theme Track dedicated to the development of applications based on Large Language Models (LLMs) for low-resource languages.
This track aims to explore innovative methodologies, architectures, and tools that leverage the power of LLMs to enhance linguistic processing, accessibility, and inclusivity for underrepresented languages. Contributions are encouraged on topics such as model adaptation and fine-tuning, multilingual and cross-lingual transfer, ethical and fairness considerations, and the creation of datasets and benchmarks that facilitate the integration of LLM-based solutions in low-resource settings.
Special Theme Track 2 -- Modern Standard Arabic (MSA) and Arabic Dialects
This special track addresses the unique challenges and opportunities in processing Modern Standard Arabic (MSA) and the rich landscape of Arabic dialects. The diglossic nature of Arabic, where the formal MSA coexists with numerous, widely used spoken dialects, presents a significant hurdle for NLP. While MSA is relatively well-resourced, Arabic dialects are quintessential examples of low-resource languages, often lacking standardised orthographies, annotated corpora, and dedicated processing tools. This track invites submissions on novel research and resources aimed at bridging this gap and advancing the state of the art in Arabic language technology. Topics of interest include, but are not limited to:
* Dialect identification and classification * Creation of corpora and lexical resources for Arabic dialects * Machine translation between MSA and dialects, and across different dialects * Speech recognition and synthesis for dialectal Arabic * Computational modelling of morphology, syntax, and semantics for dialects * NLP applications (e.g., sentiment analysis, NER) for dialectal user-generated content * Code-switching between Arabic dialects, MSA, and other languages
Submissions and Publication
_LaTeLL'2026_ welcomes high-quality submissions in English, which may take one of the following two forms:
* Regular (long) papers:Up to eight (8) pages in length, presenting substantial, original, completed, and unpublished research. * Short (poster) papers:Up to four (4) pages in length, suitable for concise or focused contributions, ongoing research, negative results, system demonstrations, and similar work. Short papers will be presented during a dedicated poster session.
The conference will not consider submissions consisting of abstracts only.
All accepted papers (both long and short) will be published as electronic proceedings (with ISBN) and made available on the conference website at the time of the event. The organisers intend to submit the proceedings for inclusion in the ACL Anthology.
Authors of papers receiving exceptionally positive reviews will be invited to prepare extended and substantially revised versions for submission to a leading journal in the field of Natural Language Processing (NLP).
Further details regarding the submission process will be provided in the follow up Calls for Papers.
The conference will also feature a Student Workshop, and awards will be presented to the authors of outstanding papers.
Important dates
* Submissions due: 1 May 2026 * Reviewing process: 20 May - 20 June 2026 * Notification of acceptance: 25 June 2026 * Camera-ready due: 10 July 2026 * Conference camera-ready proceedings ready 10 July 2026 * Conference: 30 September, 1 October and 2 October 2026
Organisation
Conference Chair
Ruslan Mitkov (Lancaster University and University of Alicante)
Programme Committee Chairs
Saad Ezzini (King Fahd University of Petroleum & Minerals)
Salima Lamsiyah (University of Luxembourg)
Tharindu Ranasinghe (Lancaster University)
Organising Committee
Maram Alharbi (Lancaster University)
Salmane Chafik (Mohammed VI Polytechnic University)
Ernesto Estevanell (University of Alicante)
Further information and contact details
The follow-up calls will provide more details on the conference venue and list keynote speakers and members of the programme committee once confirmed.
The conference website is www.latell.org/2026/ [1] and will be updated on a regular basis. For further information, please email 2026@latell.org
Registration will open in March 2026.