52 citations · 88 across the 3 of their papers we have counts for
7 papers
KinyaColBERT: A Lexically Grounded Retrieval Model for Low-Resource Retrieval-Augmented Generation
Antoine Nzeyimana, Andre Niyongabo Rubungo
The recent mainstream adoption of large language model (LLM) technology is enabling novel applications in the form of chatbots and virtual assistants across many domains. With the…
LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction
Andre Niyongabo Rubungo, Kangming Li, Jason Hattrick-Simpers +1
Large language models (LLMs) are increasingly being used in materials science. However, little attention has been given to benchmarking and standardized evaluation for LLM-based ma…
LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions
Andre Niyongabo Rubungo, Craig Arnold, Barry P. Rand +1
The prediction of crystal properties plays a crucial role in the crystal design process. Current methods for predicting crystal properties focus on modeling crystal structures usin…
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal +53
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of auto…
MasakhaNER: Named Entity Recognition for African Languages
David Ifeoluwa Adelani, Jade Abbott, Graham Neubig +58
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named en…
Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages
Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila +45
Research in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved. "Low-resourced"-ness is a compl…