Language Understanding Task

Language understanding tasks aim to enable computers to comprehend and interpret human language, focusing on diverse applications like question answering, translation, and sentiment analysis. Current research emphasizes improving the performance and robustness of large language models (LLMs), particularly transformer-based architectures, through techniques like fine-tuning, curriculum learning, and prompt engineering, often incorporating external knowledge sources or addressing biases. These advancements are crucial for enhancing the reliability and efficiency of numerous applications, ranging from improved search engines and chatbots to more sophisticated medical diagnosis support systems.