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Parametric Computer-Aided Design (CAD) is central to contemporary mechanical design.
Camba, J.D., Contero, M., Company, P.: Parametric cad modeling: An analysis of strategies for design reusability. Computer-Aided Design 74
2016
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2016
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2017
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Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. Advances in neural information processing systems 30
2017
Earlier work this paper cites.
Lindsay, A., Paterson, A., Graham, I.: Identifying and quantifying inefficiencies within industrial parametric cad models. In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research. vol. 8, p. 227 (2018)
2018
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Kenton, J.D.M.W.C., Toutanova, L.K.: Bert: Pre-training of deep bidirectional transformers for language understanding. In: Proceedings of naacL-HLT. vol. 1, p. 2 (2019)
2019
Earlier work this paper cites.
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.: Language models are few-shot learners. Advances in neural information processing systems 33
2020
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Floridi, L., Chiriatti, M.: Gpt-3: Its nature, scope, limits, and consequences. Minds and Machines 30
2020
Earlier work this paper cites.
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., Liu, P.J.: Exploring the limits of transfer learning with a unified text-to-text transformer. The Journal of Machine Learning Research 21
2020
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2020
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Ganin, Y., Bartunov, S., Li, Y., Keller, E., Saliceti, S.: Computer-aided design as language (2021)
2021
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Li, J., Selvaraju, R., Gotmare, A., Joty, S., Xiong, C., Hoi, S.C.H.: Align before fuse: Vision and language representation learning with momentum distillation. Advances in neural information processing systems 34
2021
Cited alongside, same era.
Para, W., Bhat, S., Guerrero, P., Kelly, T., Mitra, N., Guibas, L.J., Wonka, P.: Sketchgen: Generating constrained cad sketches. Advances in Neural Information Processing Systems 34
2021
Cited alongside, same era.
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.: Learning transferable visual models from natural language supervision. In: International conference on machine learning. pp. 8748–8763. PMLR (2021)
2021
Cited alongside, same era.
Seff, A., Zhou, W., Richardson, N., Adams, R.P.: Vitruvion: A generative model of parametric cad sketches. In: International Conference on Learning Representations (2021)
2021
Cited alongside, same era.
Xue, L., Barua, A., Constant, N., Al-Rfou, R., Narang, S., Kale, M., Roberts, A., Raffel, C.: Byt5: Towards a token-free future with pre-trained byte-to-byte models. Transactions of the Association for Computational Linguistics 10
2022
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2023
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2023
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Jones, B.T., Hu, M., Kodnongbua, M., Kim, V.G., Schulz, A.: Self-supervised representation learning for cad. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 21327–21336 (2023)
2023
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Willis, K.D., Jayaraman, P.K., Lambourne, J.G., Chu, H., Pu, Y.: Engineering sketch generation for computer-aided design. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2105–2114 (2021)
2021
Cited alongside, same era.
Wu, R., Xiao, C., Zheng, C.: Deepcad: A deep generative network for computer-aided design models. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 6772–6782 (2021)
2021
Cited alongside, same era.
2022
Cited alongside, same era.
He, K., Chen, X., Xie, S., Li, Y., Dollár, P., Girshick, R.: Masked autoencoders are scalable vision learners. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 16000–16009 (2022)
2022
Cited alongside, same era.
Li, J., Li, D., Xiong, C., Hoi, S.: Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation. In: International Conference on Machine Learning. pp. 12888–12900. PMLR (2022)
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Xu, X., Willis, K.D., Lambourne, J.G., Cheng, C.Y., Jayaraman, P.K., Furukawa, Y.: Skexgen: Autoregressive generation of cad construction sequences with disentangled codebooks. In: International Conference on Machine Learning. pp. 24698–24724. PMLR (2022)
2022
Cited alongside, same era.
Li, P., Guo, J., Zhang, X., Yan, D.M.: Secad-net: Self-supervised cad reconstruction by learning sketch-extrude operations. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 16816–16826 (2023)
2023
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2023
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2023
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2023
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2023
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2023
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