mlsanityData to 7 Oct 2026

PLLM: Pseudo-Labeling Large Language Models for CAD Program Synthesis

arXiv 2602.12561 ↗First posted 13 Feb 2026cs.CVcited by 0

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Abstract (arXiv)

Recovering Computer-Aided Design (CAD) programs from 3D geometries is a widely studied problem. Recent advances in large language models (LLMs) have enabled progress in CAD program synthesis, but existing methods rely on supervised training with paired shape-program data, which is often unavailable. We introduce PLLM, a self-training framework for CAD program synthesis from unlabeled 3D shapes. Given a pre-trained CAD-capable LLM and a shape dataset, PLLM iteratively samples candidate programs, selects high-fidelity executions, and augments programs to construct synthetic program-shape pairs for fine-tuning. We experiment on adapting CAD-Recode from DeepCAD to the unlabeled ABC dataset show consistent improvements in geometric fidelity and program diversity.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 37 of its 55 references that are in the map. First posted on arXiv 13 Feb 2026.

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37 of 55 references.

References · 37

  1. 2016Asynchronous Methods for Deep Reinforcement Learningcited by 2,218
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  12. 2024CAD-MLLM: Unifying Multimodality-Conditioned CAD Generation With MLLMcited by 74
25 more
  1. 2017Learning to Infer Graphics Programs from Hand-Drawn Imagescited by 73
  2. 2019Learning to Infer and Execute 3D Shape Programscited by 68
  3. 2025CAD-Llama: Leveraging Large Language Models for Computer-Aided Design Parametric 3D Model Generationcited by 65
  4. 2024CAD-Recode: Reverse Engineering CAD Code from Point Cloudscited by 63
  5. 2024CAD-SIGNet: CAD Language Inference from Point Clouds using Layer-wise Sketch Instance Guided Attentioncited by 62
  6. 2024Generating CAD Code with Vision-Language Models for 3D Designscited by 61
  7. 2021Point2Cyl: Reverse Engineering 3D Objects from Point Clouds to Extrusion Cylinderscited by 59
  8. 2025CAD-Coder: Text-to-CAD Generation with Chain-of-Thought and Geometric Rewardcited by 53
  9. 2024CAD-GPT: Synthesising CAD Construction Sequence with Spatial Reasoning-Enhanced Multimodal LLMscited by 52
  10. 2021Inferring CAD Modeling Sequences Using Zone Graphscited by 50
  11. 2025Text-to-CAD Generation Through Infusing Visual Feedback in Large Language Modelscited by 43
  12. 2022Reconstructing editable prismatic CAD from rounded voxel modelscited by 41
  13. 2023How Can Large Language Models Help Humans in Design and Manufacturing?cited by 41
  14. 2024CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solverscited by 40
  15. 2023Point2CAD: Reverse Engineering CAD Models from 3D Point Cloudscited by 33
  16. 2022CADOps-Net: Jointly Learning CAD Operation Types and Steps from Boundary-Representationscited by 30
  17. 2024Query2CAD: Generating CAD models using natural language queriescited by 28
  18. 2023ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitivescited by 22
  19. 2020PLAD: Learning to Infer Shape Programs with Pseudo-Labels and Approximate Distributionscited by 19
  20. 2025Large Language Models for Computer-Aided Design: A Surveycited by 16
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  22. 2023Improving Unsupervised Visual Program Inference with Code Rewriting Familiescited by 10
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  24. 2024BRep Boundary and Junction Detection for CAD Reverse Engineeringcited by 4
  25. 2024Leveraging Vision-Language Models for Manufacturing Feature Recognition in CAD Designscited by 4

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