Beyond Limits: Unifying Strategies to Amplify Transformer Models

Enriching Computational Workspaces across Machine Learning Domains

Introduction

Transformers have become a cornerstone in machine learning, particularly in natural language processing (NLP) and to some extent in computer vision (CV). However, as applications diversify, the limitations of transformers become apparent. Researchers from different domains have proposed a unifying solution: augmenting transformers with strategic components to enhance…