Translation Metric

Machine translation (MT) metrics automatically assess translation quality, aiming to correlate with human judgment and provide actionable insights into system performance. Current research focuses on improving the interpretability of these metrics, addressing their limitations in handling diverse linguistic phenomena (like dialects and adversarial attacks), and developing more robust methods for evaluating them across various datasets and downstream tasks. This work is crucial for advancing MT technology, enabling more reliable system evaluation and ultimately leading to higher-quality translations in practical applications.