FlowPlace
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FlowPlace: Flow Matching for Chip Placement
arXiv:2604.23658v2 Announce Type: replace Abstract: Chip placement plays an important role in physical design. While generative models like diffusion models offer promising learning-based solutions, current methods have the following limitations: they use random synthetic data for pre-training, require long sampling times, and often result in overlaps due to their dependence on gradient-based solvers during the sampling process.