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Related papers: B-repLer: Language-guided Editing of CAD Models

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Computer-Aided Design (CAD) is essential in industrial design, but the complexity of traditional CAD modeling and workflows presents significant challenges for automating the generation of high-precision, editable CAD models. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Ke Niu , Haiyang Yu , Zhuofan Chen , Zhengtao Yao , Weitao Jia , Xiaodong Ge , Jingqun Tang , Benlei Cui , Bin Li , Xiangyang Xue

Boundary representation (B-rep) is the industry standard for computer-aided design (CAD). While deep learning shows promise in processing B-rep models, existing methods suffer from a representation gap: continuous approaches offer…

Machine Learning · Computer Science 2026-02-10 Yuanxu Sun , Yuezhou Ma , Haixu Wu , Guanyang Zeng , Muye Chen , Jianmin Wang , Mingsheng Long

Large language models (LLMs) have made tremendous progress in natural language understanding and they have also been successfully adopted in other domains such as computer vision, robotics, reinforcement learning, etc. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Reza Pourreza , Apratim Bhattacharyya , Sunny Panchal , Mingu Lee , Pulkit Madan , Roland Memisevic

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…

We present ReCAD, a reinforcement learning (RL) framework that bootstraps pretrained large models (PLMs) to generate precise parametric computer-aided design (CAD) models from multimodal inputs by leveraging their inherent generative…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Jiahao Li , Yusheng Luo , Yunzhong Lou , Xiangdong Zhou

The design of man-made objects is dominated by computer aided design (CAD) tools. Assisting design with data-driven machine learning methods is hampered by lack of labeled data in CAD's native format; the parametric boundary representation…

Computer Vision and Pattern Recognition · Computer Science 2022-10-21 Benjamin T. Jones , Michael Hu , Vladimir G. Kim , Adriana Schulz

The field of Computer-Aided Design (CAD) generation has made significant progress in recent years. Existing methods typically fall into two separate categories: parametric CAD modeling and direct boundary representation (B-Rep) synthesis.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Jiahao Li , Qingwang Zhang , Qiuyu Chen , Guozhan Qiu , Yunzhong Lou , Xiangdong Zhou

We present Cephalo, a series of multimodal vision large language models (V-LLMs) designed for materials science applications, integrating visual and linguistic data for enhanced understanding. A key innovation of Cephalo is its advanced…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Markus J. Buehler

Graphics design is important for various applications, including movie production and game design. To create a high-quality scene, designers usually need to spend hours in software like Blender, in which they might need to interleave and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Ian Huang , Guandao Yang , Leonidas Guibas

The construction of CAD models has traditionally relied on labor-intensive manual operations and specialized expertise. Recent advances in large language models (LLMs) have inspired research into text-to-CAD generation. However, existing…

Computation and Language · Computer Science 2026-04-23 Jiyuan An , Jiachen Zhao , Fan Chen , Liner Yang , Zhenghao Liu , Hongyan Wang , Weihua An , Meishan Zhang , Erhong Yang

Recently, Large Language Models (LLMs) have achieved significant success, prompting increased interest in expanding their generative capabilities beyond general text into domain-specific areas. This study investigates the generation of…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Jiahao Li , Weijian Ma , Xueyang Li , Yunzhong Lou , Guichun Zhou , Xiangdong Zhou

The rapid advancement of large language models (LLMs) and multimodal learning has transformed digital content creation and manipulation. Traditional visual editing tools require significant expertise, limiting accessibility. Recent strides…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Thanh Tam Nguyen , Zhao Ren , Trinh Pham , Thanh Trung Huynh , Phi Le Nguyen , Hongzhi Yin , Quoc Viet Hung Nguyen

Instruction-based text editing is increasingly critical for real-world applications such as code editors (e.g., Cursor), but Large Language Models (LLMs) continue to struggle with this task. Unlike free-form generation, editing requires…

Computation and Language · Computer Science 2025-12-16 Yiming Zeng , Jinghan Cao , Zexin Li , Wanhao Yu , Zhankai Ye , Dawei Xiang , Ting Hua , Xin Liu , Shangqian Gao , Tingting Yu

Since ancient times, mechanical design aids have been developed to assist human users, aimed at improving the efficiency and effectiveness of design. However, even with the widespread use of contemporary Computer-Aided Design (CAD) systems,…

Computational Engineering, Finance, and Science · Computer Science 2024-08-06 Jiaxing Lu , Heran Li , Fangwei Ning , Yixuan Wang , Xinze Li , Yan Shi

Combining Vision Large Language Models (VLLMs) with diffusion models offers a powerful method for executing image editing tasks based on human language instructions. However, language instructions alone often fall short in accurately…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Tianshuo Yuan , Yuxiang Lin , Jue Wang , Zhi-Qi Cheng , Xiaolong Wang , Jiao GH , Wei Chen , Xiaojiang Peng

Recently, knowledge editing on large language models (LLMs) has received considerable attention. Compared to this, editing Large Vision-Language Models (LVLMs) faces extra challenges from diverse data modalities and complicated model…

Computation and Language · Computer Science 2024-10-30 Han Huang , Haitian Zhong , Tao Yu , Qiang Liu , Shu Wu , Liang Wang , Tieniu Tan

Large Language Models (LLMs) are revolutionizing industries by enhancing efficiency, scalability, and innovation. This paper investigates the potential of LLMs in automating Computer-Aided Design (CAD) workflows, by integrating FreeCAD with…

Human-Computer Interaction · Computer Science 2025-08-05 Sumit Kumar , Sarthak Kapoor , Harsh Vardhan , Yao Zhao

Computer-Aided Design (CAD) is an expert-level task that relies on long-horizon reasoning and coherent modeling actions. Large Language Models (LLMs) have shown remarkable advancements in enabling language agents to tackle real-world tasks.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Yifei Gong , Xing Wu , Wenda Liu , Kang Tu

This paper aims to design a unified Computer-Aided Design (CAD) generation system that can easily generate CAD models based on the user's inputs in the form of textual description, images, point clouds, or even a combination of them.…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Jingwei Xu , Chenyu Wang , Zibo Zhao , Wen Liu , Yi Ma , Shenghua Gao

Large Language Models (LLMs) power numerous AI applications, yet updating their knowledge remains costly. Model editing provides a lightweight alternative through targeted parameter modifications, with meta-learning-based model editing…

Computation and Language · Computer Science 2026-01-30 Xiaopeng Li , Shasha Li , Xi Wang , Shezheng Song , Bin Ji , Shangwen Wang , Jun Ma , Xiaodong Liu , Mina Liu , Jie Yu