David Ifeoluwa Adelani

henok.ademtew@mila.quebec

Biographie

David Adelani est professeur adjoint en science informatique et lutte contre les inégalités à l’Université McGill, et membre académique principal à Mila – Institut québécois d'intelligence artificielle. Ses recherches se concentrent sur le traitement multilingue du langage naturel, avec un accent particulier sur les langues sous-dotées en ressources.

Étudiants actuels

Henok Ademtew

Maîtrise recherche - McGill

Maîtrise recherche - McGill

victor.akinode@mila.quebec

virginia.ceccatelli@mila.quebec

Virginia Ceccatelli

Collaborateur·rice de recherche - McGill

luel.hagos-beyene@mila.quebec

David Guzmán Ramírez

Doctorat - McGill

david.guzman@mila.quebec

Stagiaire de recherche - McGill

Stagiaire de recherche - McGill

nicolas.helmeyer@mila.quebec

Yejin Jeon

Postdoctorat - McGill

yejin.jeon@mila.quebec

Senyu Li Li

Doctorat - McGill

senyu.li@mila.quebec

Mona Liu

Stagiaire de recherche - McGill

mona.liu@mila.quebec

marie.maltais@mila.quebec

Yinhan Lu

Maîtrise recherche - UdeM

Superviseur⋅e principal⋅e :

Bang Liu

yinhan.lu@mila.quebec

Doctorat - McGill

damaris-stephanie.ndjebayi@mila.quebec

Damaris Stephanie NDJEBAYI

Doctorat - McGill

Tolúlọpẹ Ògúnrẹ̀mí

Stagiaire de recherche - Standford University

tolulope.ogunremi@mila.quebec

Juhyun Oh

Collaborateur·rice alumni - McGill

juhyun.oh@mila.quebec

alessio.tosolini@mila.quebec

Jessica Ojo

Maîtrise recherche - McGill

jessica.ojo@mila.quebec

Stagiaire de recherche - McGill

pablo.tellez@mila.quebec

Alessio Tosolini

Stagiaire de recherche - McGill

Kosei Uemura

Stagiaire de recherche - McGill

kosei.uemura@mila.quebec

Vivek Verma

Maîtrise professionnelle - UdeM

vivek.verma@mila.quebec

Jessica Wang

Stagiaire de recherche - McGill

jessica.wang@mila.quebec

Tianyou Xie

Stagiaire de recherche - McGill

tianyou.xie@mila.quebec

Tianyi Xu Xu

Stagiaire de recherche - McGill

tiany12138@gmail.com

Peter Yu

Collaborateur·rice alumni - McGill

Publications

AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages

Hao Yu

Tianyi Xu

Michael A. Hedderich

Wassim Hamidouche

Syed Waqas Zamir

2026-01-09

ArXiv (prépublication)

Afri-MCQA: Multimodal Cultural Question Answering for African Languages

Atnafu Lambebo Tonja

Srija Anand

Emilio Villa Cueva

Israel Abebe Azime

Jesujoba Oluwadara Alabi

Muhidin A. Mohamed

Debela Desalegn Yadeta

Negasi Haile Abadi

Abigail Oppong

Nnaemeka Casmir Obiefuna

Idris Abdulmumin

Naome Etori

Eric Peter Wairagala

Kanda Patrick Tshinu

Imanigirimbabazi Emmanuel

Gabofetswe Malema

Alham Fikri Aji

Thamar Solorio

Africa is home to over one-third of the world's languages, yet remains underrepresented in AI research. We introduce Afri-MCQA, the first Mu… (voir plus)ltilingual Cultural Question-Answering benchmark covering 7.5k Q&A pairs across 15 African languages from 12 countries. The benchmark offers parallel English-African language Q&A pairs across text and speech modalities and was entirely created by native speakers. Benchmarking large language models (LLMs) on Afri-MCQA shows that open-weight models perform poorly across evaluated cultures, with near-zero accuracy on open-ended VQA when queried in native language or speech. To evaluate linguistic competence, we include control experiments meant to assess this specific aspect separate from cultural knowledge, and we observe significant performance gaps between native languages and English for both text and speech. These findings underscore the need for speech-first approaches, culturally grounded pretraining, and cross-lingual cultural transfer. To support more inclusive multimodal AI development in African languages, we release our Afri-MCQA under academic license or CC BY-NC 4.0 on HuggingFace (https://huggingface.co/datasets/Atnafu/Afri-MCQA)

2026-01-08

ArXiv (prépublication)

Ibom NLP: A Step Toward Inclusive Natural Language Processing for Nigeria's Minority Languages

Oluwadara Kalejaiye

Luel Hagos Beyene

Mmekut-Mfon Gabriel Edet

A. D. Akpan

Eno-Abasi Urua

Anietie U Andy

2025-11-08

ArXiv (prépublication)

AFRIDOC-MT: Document-level MT Corpus for African Languages

Jesujoba Oluwadara Alabi

Israel Abebe Azime

Miaoran Zhang

Cristina España-Bonet

Rachel Bawden

Dawei Zhu

Clement Odoje

Idris Akinade

Iffat Maab

Davis David

Shamsuddeen Hassan Muhammad

Neo Putini

David O. Ademuyiwa

Andrew Caines

Dietrich Klakow

This paper introduces AFRIDOC-MT, a document-level multi-parallel translation dataset covering English and five African languages: Amharic, … (voir plus)Hausa, Swahili, Yor\`ub\'a, and Zulu. The dataset comprises 334 health and 271 information technology news documents, all human-translated from English to these languages. We conduct document-level translation benchmark experiments by evaluating neural machine translation (NMT) models and large language models (LLMs) for translations between English and these languages, at both the sentence and pseudo-document levels. These outputs are realigned to form complete documents for evaluation. Our results indicate that NLLB-200 achieved the best average performance among the standard NMT models, while GPT-4o outperformed general-purpose LLMs. Fine-tuning selected models led to substantial performance gains, but models trained on sentences struggled to generalize effectively to longer documents. Furthermore, our analysis reveals that some LLMs exhibit issues such as under-generation, repetition of words or phrases, and off-target translations, especially for African languages.

2025-10-31

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (publié)

Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Ahead

Jesujoba Oluwadara Alabi

Michael A. Hedderich

Dietrich Klakow

2025-10-31

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (publié)