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Millicent Ochieng

5 accepted papers

2025

IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models

David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime, Jian Yun Zhuang, Jesujoba Oluwadara Alabi, Xuanli He +21
NAACL 2025long

Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource languages. Additionally, many low-resource languages (e.g. African languages) are often evaluated only on basic text classification tasks due to the lack of appropriat…

Cited by 7Source ↗PDF ↗code ↗Scholar ↗
2024

AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages

Jiayi Wang, David Ifeoluwa Adelani, Sweta Agrawal, Marek Masiak, Ricardo Rei, Eleftheria Briakou +52
NAACL 2024long

Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, since evaluation is often performed on n-gram matching metrics such as BLEU, which typically show a weaker correlation wi…

Cited by 6Source ↗PDF ↗code ↗Scholar ↗
2024

MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks

Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, Ishaan Watts, Ashutosh Sathe, Millicent Ochieng +5
NAACL 2024long

There has been a surge in LLM evaluation research to understand LLM capabilities and limitations. However, much of this research has been confined to English, leaving LLM building and evaluation for non-English languages relatively unexplored. Several new LLMs have been introduced recently, necessit…

Cited by 46Source ↗PDF ↗code ↗Scholar ↗
2023

MEGA: Multilingual Evaluation of Generative AI

Kabir Ahuja, Harshita Diddee, Rishav Hada, Millicent Ochieng, Krithika Ramesh, Prachi Jain +6
EMNLP 2023long main

Generative AI models have shown impressive performance on many Natural Language Processing tasks such as language understanding, reasoning, and language generation. An important question being asked by the AI community today is about the capabilities and limits of these models, and it is clear that…

Cited by 0Source ↗Scholar ↗
2022

A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation

David Ifeoluwa Adelani, Jesujoba Oluwadara Alabi, Angela Fan, Julia Kreutzer, Xiaoyu Shen, Machel Reid +39
NAACL 2022long

Recent advances in the pre-training for language models leverage large-scale datasets to create multilingual models. However, low-resource languages are mostly left out in these datasets. This is primarily because many widely spoken languages that are not well represented on the web and therefore ex…

Cited by 54Source ↗PDF ↗code ↗Scholar ↗