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arXiv Computer Vision By Yan Wang, Xinyi Hou, Weiguo Lin, Junjun Si, Siwei Ma

T2LSC-Bench: Benchmarking Localized Semantic Control in Text-to-Image Generation

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T2LSC-Bench is a new benchmark for evaluating localized semantic control in text-to-image generation, consisting of 50 seed subjects and 1,200 prompt cases per model, producing 7,160 images across six models. The benchmark measures Text-at-Anchor Accuracy, Semantic Subject Preservation, Semantic Leakage Rate, and Conditional Semantic Leakage Rate using a dual‑branch protocol that combines OCR‑VLM verification with structured VLM semantic judgments. Results show that while accurate text rendering remains high, semantic leakage can increase dramatically under stress‑test conditions, and anti‑leakage prompting can reduce leakage without harming rendering accuracy.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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