LithoDreamer: A Physics-Informed World Model for Multi-Stage Computational Lithography
Yuqi Jiang, Yumeng Liu, Zimu Li, Jinyuan Deng, Qian Jin, Yucheng Cui, YU LI, Xunzhao Yin, Qi Sun, Cheng Zhuo
摘要
As semiconductor technology nodes scale, computational lithography is essential for ensuring yield and performance. However, lithography is a continuous physical process involving mask optimization, optical imaging, resist exposure, and development, which existing models fail to capture. To overcome this limitation, we present LithoDreamer, the first physics-informed World Model (WM) framework for computational lithography, which formulates the "Layout-Mask-Resist Image-After Development Image (ADI)" pipeline as a decision-driven multi-step evolution system. LithoDreamer captures feature changes between adjacent states to model stage-specific physicsinformed latent spaces, in which it controls process intervention exploration and drives subsequent state transitions. To achieve interpretable intervention optimization without continuous supervision, we propose a contrastive variational optimization paradigm that contrasts the latent differences between intervention paths with variational evolution constraints, guiding the model to generate evolutions consistent with real lithography physics. Experiments show LithoDreamer achieves state-of-the-art performance in forward evolution and inverse planning. Our lithography dataset is publicly available at GitHub .
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper7
- An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleAlexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn 等ICLR 2021 · 被引用 21,477 次
- Scalable Diffusion Models with TransformersWilliam Peebles, Saining XieICCV 2023 · 被引用 5,568 次
- Diffusion for World Modeling: Visual Details Matter in AtariEloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto 等NeurIPS 2024 · 被引用 359 次
- Intelligent OPC Engineer Assistant for Semiconductor ManufacturingGuojin Chen, Haoyu Yang, Bei Yu, Haoxing RenAAAI 2025 · 被引用 4 次
- Feature Purification Matters: Suppressing Outlier Propagation for Training-Free Open-Vocabulary Semantic SegmentationShuo Jin, Siyue Yu, Bingfeng Zhang, Mingjie Sun 等ICCV 2025 · 被引用 3 次
相关 Paper
- Optical Diffraction-based Convolution for Semiconductor LithographyYoung-Han Son, Dong-Hee Shin, Deok-Joong Lee, Hyun Jung Lee 等CVPR 2026
- LithoGRPO: Fast Inverse Lithography via GRPO Reinforced Flow MatchingYao Lai, Xuyuan Xiong, Zeyue Xue, Guojin Chen 等ICML 2026
- TokMan: Tokenize Manhattan Mask Optimization for Inverse LithographyYiwen Wu, Yuyang Chen, Ye Xia, Yao Zhao 等NeurIPS 2025 · 被引用 1 次
- 3DID: Direct 3D Inverse Design for Aerodynamics with Physics-Aware OptimizationYuze Hao, Linchao Zhu, Yi YangNeurIPS 2025 · 被引用 3 次
- ILILT: Implicit Learning of Inverse Lithography TechnologiesHaoyu Yang, Haoxing RenICML 2024 · 被引用 10 次
