苹果研究新方法评估视频字幕质量
Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering
苹果搞了个新方法，用多选题来测试视频字幕质量，比传统方法更科学，能避免因为用词不同就扣分。
苹果提出通过多选题测试视频字幕质量，解决现有评估依赖参考文本匹配的缺陷。新方法基于信息保真度，避免因词汇差异或视觉焦点变化对高质量字幕的惩罚。评估过程能提供更精细的质量分析。
Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering
Evaluating video captioning remains a critical challenge for Visual Large Language Models (VLLMs). Existing metrics primarily rely on matching generated text against ground-truth references. This paradigm suffers from the “one-to-many” nature of video description, where high-quality captions are often penalized for lexical mismatches or valid shifts in visual focus. Furthermore, such assessments are typically one-dimensional, failing to provide a fine-grained analysis of caption quality. To address this, we redefine caption quality via information fidelity: A caption must maximize the coverage…
