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arXiv · 2511.10255

Unitho: A Unified Multi-Task Framework for Computational Lithography

Qian Jin·Yumeng Liu·Yuqi Jiang·Qi Sun·Cheng Zhuo
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Abstract

Reliable, generalizable data foundations are critical for enabling large-scale models in computational lithography. However, essential tasks-mask generation, rule violation detection, and layout optimization-are often handled in isolation, hindered by scarce datasets and limited modeling approaches. To address these challenges, we introduce Unitho, a unified multi-task large vision model built upon the Transformer architecture. Trained on a large-scale industrial lithography simulation dataset with hundreds of thousands of cases, Unitho supports end-to-end mask generation, lithography simulation, and rule violation detection. By enabling agile and high-fidelity lithography simulation, Unitho further facilitates the construction of robust data foundations for intelligent EDA. Experimental results validate its effectiveness and generalizability, with performance substantially surpassing academic baselines.

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Qian Jin, Yumeng Liu, Yuqi Jiang, Qi Sun, Cheng Zhuo. 2025-11-13. Unitho: A Unified Multi-Task Framework for Computational Lithography. https://arxiv.org/abs/2511.10255

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