3 citations · 6 across the 3 of their papers we have counts for
3 papers
What Happens When Small Is Made Smaller? Exploring the Impact of Compression on Small Data Pretrained Language Models
Busayo Awobade, Mardiyyah Oduwole, Steven Kolawole
Compression techniques have been crucial in advancing machine learning by enabling efficient training and deployment of large-scale language models. However, these techniques have…
Vision Transformers for Mobile Applications: A Short Survey
Nahid Alam, Steven Kolawole, Simardeep Sethi +2
Vision Transformers (ViTs) have demonstrated state-of-the-art performance on many Computer Vision Tasks. Unfortunately, deploying these large-scale ViTs is resource-consuming and i…
Adapting to the Low-Resource Double-Bind: Investigating Low-Compute Methods on Low-Resource African Languages
Colin Leong, Herumb Shandilya, Bonaventure F. P. Dossou +10
Many natural language processing (NLP) tasks make use of massively pre-trained language models, which are computationally expensive. However, access to high computational resources…