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SCALE: Self-Supervised Constraint-Aware Layout GEneration for Local P&R DRV Fixing at Advanced Nodes

First seen · 7/24/2026, 06:38 AMLatest activity · 7/24/2026, 06:38 AM

SCALE targets local place-and-route design-rule violation repair at sub-2nm nodes. It serializes multi-layer BEOL geometry as structured text and self-supervises a language model by reconstructing randomly masked polygons. Natural-language constraints and high-temperature sampling then produce candidate layouts, which an industrial signoff DRC checker labels for training a domain-adapted DRC-VLM. According to the abstract, its geometric guidance improves existing repair agents’ solve rates by 12–25 percentage points, reaching up to 97% across 100 real cases involving enclosure, spacing, width, and color-spacing violations.

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  1. AggregatorarXiv7/24, 06:38 AMnot independentRepresentative
    SCALE: Self-Supervised Constraint-Aware Layout GEneration for Local P&R DRV Fixing at Advanced Nodes