研究人员推出了一项名为COHERENCE的新基准测试，旨在评估多模态大型语言模型（MLLM）的细粒度图像-文本对齐能力。现有的基准测试常常忽略真实文档中交错图像-文本上下文的复杂性。COHERENCE通过评估MLLM在混合媒体环境中连接视觉和文本信息的能力来弥补这一不足，涵盖四个不同领域，包含超过6000个问题。 AI
影响 为多模态模型提供了一个新的评估框架，突出了当前在理解交错图像-文本数据方面的局限性。
排序理由 这是一篇介绍AI模型评估新基准的研究论文。
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arXiv:2604.27389v1 Announce Type: cross Abstract: In recent years, Multimodal Large Language Models (MLLMs) have achieved remarkable progress on a wide range of multimodal benchmarks. Despite these advances, most existing benchmarks mainly focus on single-image or multi-image com…
In recent years, Multimodal Large Language Models (MLLMs) have achieved remarkable progress on a wide range of multimodal benchmarks. Despite these advances, most existing benchmarks mainly focus on single-image or multi-image comprehension. In real-world scenarios such as docume…