CADReview: Automatically Reviewing CAD Programs with Error Detection and Correction
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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
- 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 8,065
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- 2018PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understandingcited by 526
- 2023Self-Edit: Fault-Aware Code Editor for Code Generationcited by 111
9 more
- 2024CAD-SIGNet: CAD Language Inference from Point Clouds using Layer-wise Sketch Instance Guided Attentioncited by 64
- 2024CAD-GPT: Synthesising CAD Construction Sequence with Spatial Reasoning-Enhanced Multimodal LLMscited by 53
- 2024CadVLM: Bridging Language and Vision in the Generation of Parametric CAD Sketchescited by 28
- 2023ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitivescited by 23
- 2023CADTalk: An Algorithm and Benchmark for Semantic Commenting of CAD Programscited by 15
- 2022Joint Multimodal Entity-Relation Extraction Based on Edge-enhanced Graph Alignment Network and Word-pair Relation Taggingcited by 14
- 2024Coffee-Gym: An Environment for Evaluating and Improving Natural Language Feedback on Erroneous Codecited by 9
- 2024Learning to Correction: Explainable Feedback Generation for Visual Commonsense Reasoning Distractorcited by 7
- 2024FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Modelscited by 6
Built on by
Citing papers per year: 2026: 4.
4 papers.
- 2026Beyond NL2Code: A Structured Survey of Multimodal Code Intelligencecited by 6
- 2026BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoningcited by 3
- 2026BRepCLIP: Contrastive Multimodal Pretraining on BRep Primitives for CAD Understandingcited by 1
- 2026RA-CAD: Learning Post-Execution Critique for State-Aware Text-to-CAD Generationcited by 0
- 2026RA-CAD: Learning Post-Execution Critique for State-Aware Text-to-CAD Generation6 Aug 2026
- 2026Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence14 Jun 2026
- 2026BRepCLIP: Contrastive Multimodal Pretraining on BRep Primitives for CAD Understanding3 Jun 2026
- 2026BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoning25 Feb 2026
Similar, not cited
Close in wording, no citation either way
- 2026CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation
- 2026BenchCAD: A Comprehensive, Industry-Standard Benchmark for Programmatic CAD
- 2025CAD-Coder: An Open-Source Vision-Language Model for Computer-Aided Design Code Generation
- 2026CADFS: A Big CAD Program Dataset and Framework for Computer-Aided Design with Large Language Models
- 2026CADSmith: Multi-Agent CAD Generation with Programmatic Geometric Validation
- 2026Foundation Models for Automatic CAD Generation
- 2026GIFT: Bootstrapping Image-to-CAD Program Synthesis via Geometric Feedback
- 2026MUSE: Benchmarking Manufacturable, Functional, and Assemblable Text-to-CAD Generation