Dual Language Models: Balancing Training Efficiency and Overfitting Resilience

This article, sourced from ArXiv, likely discusses the challenges and solutions related to training dual language models. The focus is on finding a balance between efficient training processes and preventing the model from overfitting the training data, which can hinder its ability to generalize to new, unseen data. The research likely explores different techniques or architectures to achieve this balance.