TLDR
多模态实体链接将文本与图像中的实体提及关联到知识库条目。这类系统在稀有实体上性能下降，而先前工作主要通过流行度指标（如页面浏览量）衡量稀有性。我们使用知识图谱结构指标扩展了这一视角，刻画实体的被记录与被连接程度。这些指标识别出许多流行度指标遗漏的稀有实体。在由此得到的稀有实体切片上，SOTA 准确率下降 15.4–39.9%，表明不同的稀有性定义暴露不同的失效模式。为应对该问题…Multimodal entity linking grounds entity mentions in text and images to knowledge-base entries. These systems degrade on rare entities, but prior work measures rarity primarily through popularity-based metrics such as pageviews. We broaden this view using knowledge-graph structural metrics that capture how well an entity is documented and connected. These metrics identify many rare entities that popularity metrics miss. Across the resulting rare-entity slices, state-of-the-art accuracy drops by 15.4-39.9%, showing that different rarity definitions expose different failure modes. To address the