WISE (World Knowledge-Informed Semantic Evaluation) is a benchmark and dataset for evaluating text-to-image (T2I) models on their ability to integrate world knowledge and complex semantic understanding into generated images. The benchmark contains 1,000 carefully crafted prompts organized across 25 sub-domains spanning cultural common sense, spatio-temporal reasoning, and natural science. The project introduces WiScore, a quantitative metric designed to assess knowledge–image alignment beyond traditional CLIP-based metrics. The repository includes prompt JSON files (structured prompts and explanations), evaluation code and scripts, example assets, and instructions to compute WiScore and run evaluations. Code and data are hosted in the public GitHub repository (https://github.com/PKU-YuanGroup/WISE). The accompanying paper is available at arXiv:2503.07265. (Also cited as [22] in the referencing paper.)
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