Large Vision Language Models (LVLMs), despite their recent success, are hardly comprehensively tested for their cognitive abilities. Inspired by the prevalent use of the "Cookie Theft" task in human cognition test, we propose a novel evaluation benchmark to evaluate high-level cognitive ability of LVLMs using images with rich semantics. It defines eight reasoning capabilities and consists of an image description task and a visual question answering task. Our evaluation on well-known LVLMs shows that there is still a large gap in cognitive ability between LVLMs and humans.

翻译：大型视觉语言模型（LVLMs）尽管近期取得了成功，但其认知能力尚未得到全面测试。受人类认知测试中广泛采用的“饼干盗窃”任务启发，我们提出了一种新颖的评估基准，利用富含语义的图像评估LVLMs的高水平认知能力。该基准定义了八种推理能力，并包含图像描述任务和视觉问答任务。我们对知名LVLMs的评估表明，LVLMs与人类在认知能力上仍存在显著差距。