International Conference

‘LAnguage TEchnologies for Low-resource Languages’ (LaTeLL ’2026)

Fes, Morocco

30 September, 1 and 2 October 2026

www.latell.org/2026/

First 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 spectrum of topics 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 Second Call for Papers, scheduled for release in November 2025.

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/ and will be updated on a regular basis. For further information, please email 2026@latell.org


Registration will open in March 2026.