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.
T2I-ReasonBench: Benchmarking Reasoning-Informed Text-to-Image Generation
T2I-ReasonBench evaluates the reasoning capabilities of text-to-image models across four dimensions using a two-stage protocol, analyzing their performance comprehensively.
- Year
- 2025
- Venue
- arXiv 2025
- Authors
- 5
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2508.17472ARXIV-DEFAULT
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