RoBERTa Model

RoBERTa is a robustly optimized pre-trained language model frequently used as a foundation for various natural language processing tasks. Current research focuses on adapting RoBERTa, often through fine-tuning or hybrid architectures incorporating BiLSTMs, for applications like sentiment analysis, machine-generated text detection, and semantic textual relatedness across multiple languages. These efforts aim to improve model performance, address issues like misplaced confidence and bias, and enhance the efficiency and robustness of RoBERTa for diverse downstream applications, impacting fields ranging from digital epidemiology to quality assurance in engineering.