mlsanityData to 14 Oct 2026

CADReview: Automatically Reviewing CAD Programs with Error Detection and Correction

arXiv 2505.22304 ↗First posted 28 May 2025cs.CVcited by 4

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Abstract (arXiv)

Computer-aided design (CAD) is crucial in prototyping 3D objects through geometric instructions (i.e., CAD programs). In practical design workflows, designers often engage in time-consuming reviews and refinements of these prototypes by comparing them with reference images. To bridge this gap, we introduce the CAD review task to automatically detect and correct potential errors, ensuring consistency between the constructed 3D objects and reference images. However, recent advanced multimodal large language models (MLLMs) struggle to recognize multiple geometric components and perform spatial geometric operations within the CAD program, leading to inaccurate reviews. In this paper, we propose the CAD program repairer (ReCAD) framework to effectively detect program errors and provide helpful feedback on error correction. Additionally, we create a dataset, CADReview, consisting of over 20K program-image pairs, with diverse errors for the CAD review task. Extensive experiments demonstrate that our ReCAD significantly outperforms existing MLLMs, which shows great potential in design applications.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 21 of its 40 references that are in the map. First posted on arXiv 28 May 2025.

Builds on

21 of 40 references.

References · 21

  1. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 8,065
  2. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  3. 2023Improved Baselines with Visual Instruction Tuningcited by 4,418
  4. 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,234
  5. 2024LLaVA-OneVision: Easy Visual Task Transfercited by 2,719
  6. 2023MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGIcited by 2,080
  7. 2024Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scalingcited by 1,599
  8. 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,368
  9. 2023Teaching Large Language Models to Self-Debugcited by 988
  10. 2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquingcited by 783
  11. 2018PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understandingcited by 526
  12. 2023Self-Edit: Fault-Aware Code Editor for Code Generationcited by 111
9 more
  1. 2024CAD-SIGNet: CAD Language Inference from Point Clouds using Layer-wise Sketch Instance Guided Attentioncited by 64
  2. 2024CAD-GPT: Synthesising CAD Construction Sequence with Spatial Reasoning-Enhanced Multimodal LLMscited by 53
  3. 2024CadVLM: Bridging Language and Vision in the Generation of Parametric CAD Sketchescited by 28
  4. 2023ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitivescited by 23
  5. 2023CADTalk: An Algorithm and Benchmark for Semantic Commenting of CAD Programscited by 15
  6. 2022Joint Multimodal Entity-Relation Extraction Based on Edge-enhanced Graph Alignment Network and Word-pair Relation Taggingcited by 14
  7. 2024Coffee-Gym: An Environment for Evaluating and Improving Natural Language Feedback on Erroneous Codecited by 9
  8. 2024Learning to Correction: Explainable Feedback Generation for Visual Commonsense Reasoning Distractorcited by 7
  9. 2024FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Modelscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation
  2. 2026BenchCAD: A Comprehensive, Industry-Standard Benchmark for Programmatic CAD
  3. 2025CAD-Coder: An Open-Source Vision-Language Model for Computer-Aided Design Code Generation
  4. 2026CADFS: A Big CAD Program Dataset and Framework for Computer-Aided Design with Large Language Models
  5. 2026CADSmith: Multi-Agent CAD Generation with Programmatic Geometric Validation
  6. 2026Foundation Models for Automatic CAD Generation
  7. 2026GIFT: Bootstrapping Image-to-CAD Program Synthesis via Geometric Feedback
  8. 2026MUSE: Benchmarking Manufacturable, Functional, and Assemblable Text-to-CAD Generation