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Generative AI has transformed the fields of Design and Manufacturing by providing efficient and automated methods for generating and modifying 3D objects.
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Language models are few-shot learners
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Learning transferable visual models from natural language supervision
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Gabriel Poesia, Oleksandr Polozov, Vu Le, Ashish Tiwari, Gustavo Soares, Christopher Meek, and Sumit Gulwani · 2022
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Nitarshan Rajkumar, Raymond Li, and Dzmitry Bahdanau · 2022
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Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control
Sachin Kumar, T Gopi, N Harikeerthana, Munish Kumar Gupta, Vidit Gaur, Grzegorz M Krolczyk, and ChuanSong Wu · 2023
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How can large language models help humans in design and manufacturing?
Liane Makatura, Michael Foshey, Bohan Wang, Felix HähnLein, Pingchuan Ma, Bolei Deng, Megan Tjandrasuwita, Andrew Spielberg, Crystal Elaine Owens, Peter Yichen Chen, et al · 2023
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Chain-of-thought prompting elicits reasoning in large language models
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Generating sequences by learning to self-correct
Sean Welleck, Ximing Lu, Peter West, Faeze Brahman, Tianxiao Shen, Daniel Khashabi, and Yejin Choi · 2022
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Point-bert: Pre-training 3d point cloud transformers with masked point modeling
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Lion: Latent point diffusion models for 3d shape generation
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Ziyu Guo, Renrui Zhang, Xiangyang Zhu, Yiwen Tang, Xianzheng Ma, Jiaming Han, Kexin Chen, Peng Gao, Xianzhi Li, Hongsheng Li, et al · 2023
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Milin Kodnongbua, Benjamin T Jones, Maaz Bin Safeer Ahmad, Vladimir G Kim, and Adriana Schulz · 2023
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Utilizing chatgpt to assist cad design for microfluidic devices
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Deep learning-based semantic segmentation of machinable volumes for cyber manufacturing service
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Pointnorm: Dual normalization is all you need for point cloud analysis
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Learning defect prediction from unrealistic data
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