Optimizing language models to achieve both high performance and efficiency remains a
complex challenge due to the vast parameter spaces and the intricacies of text generation …

This study investigates the performance of transformer-based machine learning models,
specifically BERT, RoBERTa, and ALBERT, in multiclass text classification within the context …

Construction safety training is essential for equip** workers with the skills needed to
mitigate hazards on job sites. Traditional training methods often fail to adequately prepare …

Mobile robots are increasingly ubiquitous in modern society, necessitating more human-like
interaction capabilities, such as following operator instructions or collaborating with humans …

This study evaluates the impact of Large Language Models (LLMs) on e-commerce by
benchmarking their performance in sentiment analysis and causal inference. LLMs, such as …

In the dynamic e-commerce landscape, understanding customer feedback is essential for
optimizing business strategies and enhancing customer experiences. Traditional sentiment …