Language Correction

Language correction encompasses the automated identification and rectification of errors in text or other data modalities, aiming to improve accuracy, fluency, and overall quality. Current research focuses on leveraging large language models (LLMs) and other deep learning architectures, often incorporating techniques like chain-of-thought prompting, self-consistency checks, and multi-agent systems to enhance error detection and correction capabilities. This field is significant for advancing human-computer interaction, improving the reliability of AI systems across diverse applications (e.g., education, healthcare, robotics), and addressing challenges posed by noisy or incomplete data in various domains.