Level QE

Level Quality Estimation (QE) focuses on automatically assessing the quality of machine-translated text without needing a human-created reference translation. Current research emphasizes developing more accurate and efficient QE models, exploring various levels of analysis (word, sentence, document) and incorporating advanced techniques like transformers and large language models (LLMs) to improve performance beyond traditional handcrafted features and deep learning approaches. This work is crucial for enhancing machine translation systems and post-editing workflows, ultimately leading to faster and more accurate translation processes across multiple languages.