CAD-Refiner: A Unified Framework for CAD Generation and Iterative Editing

Computer-Aided Design (CAD) modeling underpins a wide range of industrial applications. During the conceptual design phase, designers often refine initial solutions iteratively to achieve desired results. A key goal of AI-assisted CAD is to support the full modeling workflow from initial generation to iterative refinement. However, most existing approaches treat generation and editing as separate tasks, hindering coherence and adaptability in real-world scenarios. To address this limitation, we propose CAD-Refiner, a unified framework that supports free-form multimodal inputs and enables iterative refinement over previously generated results. Specifically, we design an agent named CAD Insighter that interprets multimodal inputs into topological structure graphs, which explicitly represent the fundamental elements and their relationships within CAD objects. We then propose a carefully designed decoder architecture and a Sequence Injection Strategy (SIS) to enable multiple applications within a unified modeling framework. Furthermore, we propose CAD Checker, an error-aware feedback module that performs geometry-based reward shaping during optimization, enhancing modeling quality and geometric validity. Additionally, we introduce MMCAD, a multimodal extension of DeepCAD tailored for CAD generation and editing. Extensive experiments demonstrate the effectiveness of CAD-Refiner across multiple tasks.