BERT Like

BERT-like models, transformer-based architectures pre-trained on massive text corpora, are being adapted and improved for diverse applications beyond general natural language processing. Current research focuses on enhancing their performance in multimodal settings, handling incomplete or noisy data (like code without informative symbols), and mitigating biases inherent in training data. These advancements are significantly impacting fields ranging from financial analysis and software engineering to assistive technologies and improving the accuracy and efficiency of various NLP tasks across multiple languages.