Transformer Based Natural Language

Transformer-based natural language processing (NLP) leverages deep learning architectures to achieve state-of-the-art performance in various NLP tasks, focusing on improving model robustness, explainability, and efficiency. Current research emphasizes enhancing model resilience against adversarial attacks (including dynamic backdoors) and improving the reliability of predictions over time and across diverse languages. These advancements are significant for building more trustworthy and effective NLP systems with applications ranging from social media monitoring and medical text analysis to automated negotiation and software development.