T2i-reasonbench: Benchmarking Reasoning-informed Text-to-image Generation

Kaiyue Sun, Rongyao Fang, Chengqi Duan, Xian Liu, Xihui Liu . No Venue 2025

[Paper]    
Compositional Generalization Datasets Evaluation Visual Question Answering

We propose T2I-ReasonBench, a benchmark evaluating reasoning capabilities of text-to-image (T2I) models. It consists of four dimensions: Idiom Interpretation, Textual Image Design, Entity-Reasoning and Scientific-Reasoning. We propose a two-stage evaluation protocol to assess the reasoning accuracy and image quality. We benchmark various T2I generation models, and provide comprehensive analysis on their performances.

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