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arXiv · 2311.01361

GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks

Xinlu Zhang·Yujie Lu·Weizhi Wang·An Yan·Jun Yan·Lianke Qin·Heng Wang·Xifeng Yan·William Yang Wang·Linda Ruth Petzold
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Abstract

Automatically evaluating vision-language tasks is challenging, especially when it comes to reflecting human judgments due to limitations in accounting for fine-grained details. Although GPT-4V has shown promising results in various multi-modal tasks, leveraging GPT-4V as a generalist evaluator for these tasks has not yet been systematically explored. We comprehensively validate GPT-4V's capabilities for evaluation purposes, addressing tasks ranging from foundational image-to-text and text-to-image synthesis to high-level image-to-image translations and multi-images to text alignment. We employ two evaluation methods, single-answer grading and pairwise comparison, using GPT-4V. Notably, GPT-4V shows promising agreement with humans across various tasks and evaluation methods, demonstrating immense potential for multi-modal LLMs as evaluators. Despite limitations like restricted visual clarity grading and real-world complex reasoning, its ability to provide human-aligned scores enriched with detailed explanations is promising for universal automatic evaluator.

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Xinlu Zhang, Yujie Lu, Weizhi Wang, An Yan, Jun Yan, Lianke Qin, Heng Wang, Xifeng Yan, William Yang Wang, Linda Ruth Petzold. 2023-11-02. GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks. https://arxiv.org/abs/2311.01361

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