IterCAD is a multimodal agent framework using progressive SFT and geometry-aware RL for CAD tasks, with a new data pipeline, IterCAD-Bench, and CD-TR metric showing outperformance in executability and precision.
CADDesigner: Conceptual CAD Model Generation with a General-Purpose Agent
4 Pith papers cite this work. Polarity classification is still indexing.
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abstract
Computer-Aided Design (CAD) is widely used for conceptual design and parametric 3D modeling, but typically requires a high level of expertise from designers. To lower the entry barrier and facilitate early-stage CAD modeling, we present CADDesigner, an LLM-powered agent for conceptual CAD design. The agent accepts both textual descriptions and sketches as input, engaging in interactive dialogue with users to refine and clarify design requirements through comprehensive requirement analysis. Built upon a novel Explicit Context Imperative Paradigm (ECIP), the agent generates high-quality CAD modeling code. During the generation process, the agent incorporates iterative visual feedback to improve model quality. Generated design cases can be stored in a structured knowledge base, providing a mechanism for continual knowledge accumulation and future improvement of code generation. Experimental results show that CADDesigner achieves competitive performance and outperforms representative baselines on conceptual CAD model generation tasks.
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2026 4roles
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CAD generation agents are augmented with FEA feedback plus text blueprint and 21-view image signals, raising Box-IoU on S2O and Fusion360 while showing that base models produce no strict-passing FEA artifacts.
AADvark extends agent-aided CAD design to dynamic 3D assemblies with movable parts by integrating constraint solvers and visual feedback to create a verification signal for the agent.
citing papers explorer
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IterCAD: An Iterative Multimodal Agent for Visually-Grounded CAD Generation and Editing
IterCAD is a multimodal agent framework using progressive SFT and geometry-aware RL for CAD tasks, with a new data pipeline, IterCAD-Bench, and CD-TR metric showing outperformance in executability and precision.
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Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback
CAD generation agents are augmented with FEA feedback plus text blueprint and 21-view image signals, raising Box-IoU on S2O and Fusion360 while showing that base models produce no strict-passing FEA artifacts.
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Agent-Aided Design for Dynamic CAD Models
AADvark extends agent-aided CAD design to dynamic 3D assemblies with movable parts by integrating constraint solvers and visual feedback to create a verification signal for the agent.
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