mlsanityData to 7 Oct 2026

CADReasoner: Iterative Program Editing for CAD Reverse Engineering

arXiv 2603.29847 ↗First posted 18 Feb 2026cs.GR cs.CV cs.HCcited by 4

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Abstract (arXiv)

Computer-Aided Design (CAD) powers modern engineering, yet producing high-quality parts still demands substantial expert effort. Many AI systems tackle CAD reverse engineering, but most are single-pass and miss fine geometric details. In contrast, human engineers compare the input shape with the reconstruction and iteratively modify the design based on remaining discrepancies. Agent-based methods mimic this loop with frozen VLMs, but weak 3D grounding of current foundation models limits reliability and efficiency. We introduce CADReasoner, a model trained to iteratively refine its prediction using geometric discrepancy between the input and the predicted shape. The model outputs a runnable CadQuery Python program whose rendered mesh is fed back at the next step. CADReasoner fuses multi-view renders and point clouds as complementary modalities. To bridge the realism gap, we propose a scan-simulation protocol applied during both training and evaluation. Across DeepCAD, Fusion 360, and MCB benchmarks, CADReasoner attains state-of-the-art results on clean and scan-sim tracks.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 46 of its 63 references that are in the map. First posted on arXiv 18 Feb 2026.

Builds on

46 of 63 references.

References · 46

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34 more
  1. 2018Supervised Fitting of Geometric Primitives to 3D Point Cloudscited by 90
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.