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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

We present MeshLLM, a novel framework that leverages large language models (LLMs) to understand and generate text-serialized 3D meshes. Our approach addresses key limitations in existing methods, including the limited dataset scale when…

This work explores expanding the capabilities of large language models (LLMs) pretrained on text to generate 3D meshes within a unified model. This offers key advantages of (1) leveraging spatial knowledge already embedded in LLMs, derived…

Machine Learning · Computer Science 2024-11-15 Zhengyi Wang , Jonathan Lorraine , Yikai Wang , Hang Su , Jun Zhu , Sanja Fidler , Xiaohui Zeng

Recent Multi-Modal Large Language Models (MLLMs) have demonstrated strong capabilities in learning joint representations from text and images. However, their spatial reasoning remains limited. We introduce 3DFroMLLM, a novel framework that…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Noor Ahmed , Cameron Braunstein , Steffen Eger , Eddy Ilg

In the pursuit of efficient automated content creation, procedural generation, leveraging modifiable parameters and rule-based systems, emerges as a promising approach. Nonetheless, it could be a demanding endeavor, given its intricate…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Chunyi Sun , Junlin Han , Weijian Deng , Xinlong Wang , Zishan Qin , Stephen Gould

Large Language Models (LLMs) have demonstrated impressive capabilities in a wide range of code generation tasks. However, generating code for certain domains remains challenging. One such domain is Computer-Aided Design (CAD) program, where…

Machine Learning · Computer Science 2026-03-10 Yan-Ying Chen , Dule Shu , Matthew Hong , Andrew Taber , Jonathan Li , Matthew Klenk

Multimodal Large Language Models (MLLMs) struggle with accurately capturing camera-object relations, especially for object orientation, camera viewpoint, and camera shots. This stems from the fact that existing MLLMs are trained on images…

Designing complex computer-aided design (CAD) models is often time-consuming due to challenges such as computational inefficiency and the difficulty of generating precise models. We propose a novel language-guided framework for industrial…

Artificial Intelligence · Computer Science 2025-05-27 Jianxing Liao , Junyan Xu , Yatao Sun , Maowen Tang , Sicheng He , Jingxian Liao , Shui Yu , Yun Li , Hongguan Xiao

Generating and editing a 3D scene guided by natural language poses a challenge, primarily due to the complexity of specifying the positional relations and volumetric changes within the 3D space. Recent advancements in Large Language Models…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Yiqi Lin , Hao Wu , Ruichen Wang , Haonan Lu , Xiaodong Lin , Hui Xiong , Lin Wang

With the rapid advancement of artificial intelligence and robotics, the integration of Large Language Models (LLMs) with 3D vision is emerging as a transformative approach to enhancing robotic sensing technologies. This convergence enables…

Robotics · Computer Science 2025-11-19 Vinit Mehta , Charu Sharma , Karthick Thiyagarajan

We present LL3M, a multi-agent system that leverages pretrained large language models (LLMs) to generate 3D assets by writing interpretable Python code in Blender. We break away from the typical generative approach that learns from a…

Graphics · Computer Science 2025-08-12 Sining Lu , Guan Chen , Nam Anh Dinh , Itai Lang , Ari Holtzman , Rana Hanocka

Generating 3D models has traditionally been a complex task requiring specialized expertise. While recent advances in generative AI have sought to automate this process, existing methods produce non-editable representation, such as meshes or…

Graphics · Computer Science 2026-01-21 Fadlullah Raji , Stefano Petrangeli , Matheus Gadelha , Yu Shen , Uttaran Bhattacharya , Gang Wu

Parametric Computer-Aided Design (CAD) is central to contemporary mechanical design. However, it encounters challenges in achieving precise parametric sketch modeling and lacks practical evaluation metrics suitable for mechanical design. We…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Sifan Wu , Amir Khasahmadi , Mor Katz , Pradeep Kumar Jayaraman , Yewen Pu , Karl Willis , Bang Liu

Large Language Models are increasingly capable of interpreting multimodal inputs to generate complex 3D shapes, yet robust methods to evaluate geometric and structural fidelity remain underdeveloped. This paper introduces a human in the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-10 Ahmed R. Sadik , Mariusz Bujny

Large language models (LLMs) have demonstrated rapid progress across a wide array of domains. Owing to the very large number of parameters and training data in LLMs, these models inherently encompass an expansive and comprehensive materials…

Materials Science · Physics 2024-11-20 Siyu Liu , Tongqi Wen , A. S. L. Subrahmanyam Pattamatta , David J. Srolovitz

Large Language Models(LLMs) have revolutionized text generation and multimodal perception,but their capabilities in 3D content generation remain underexplored. Existing methods compromise by producing either low-resolution meshes or coarse…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Junming Huang , Chi Wang , Letian Li , Guangkai Xu , Donglin Huang , Hao Chen , Qiang Dai , Weiwei Xu

Generative AI models provide a wide range of tools capable of performing complex tasks in a fraction of the time it would take a human. Among these, Large Language Models (LLMs) stand out for their ability to generate diverse texts, from…

Computation and Language · Computer Science 2024-10-07 Baldomero R. Árbol , Dan Casas

Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Yining Hong , Haoyu Zhen , Peihao Chen , Shuhong Zheng , Yilun Du , Zhenfang Chen , Chuang Gan

Video generation has achieved remarkable progress in visual fidelity and controllability, enabling conditioning on text, layout, or motion. Among these, motion control - specifying object dynamics and camera trajectories - is essential for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Muhammed Burak Kizil , Enes Sanli , Niloy J. Mitra , Erkut Erdem , Aykut Erdem , Duygu Ceylan

Industry 4.0 has revolutionized manufacturing by driving digitalization and shifting the paradigm toward additive manufacturing (AM). Fused Deposition Modeling (FDM), a key AM technology, enables the creation of highly customized,…

Computation and Language · Computer Science 2026-01-01 Yayati Jadhav , Peter Pak , Amir Barati Farimani
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