Chris discusses the limitations of the Blue score in evaluating translation models and highlights the importance of having a metric that accurately reflects the improvements made by new models. He explains how the Blue score primarily focuses on local phrase-level fluency, while ignoring larger grammatical structures and long-distance dependencies. Chris emphasizes the need for metrics that align with human judgment and can capture the advancements in translation quality achieved by different models.
