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Creating Computer-Aided Design (CAD) models requires significant expertise and effort.
Inversecsg: automatic conversion of 3d models to csg trees
Du, T., Inala, J. P., Pu, Y., Spielberg, A., Schulz, A., Rus, D., Solar-Lezama, A., and Matusik, W · 2018
Earlier work this paper cites.
Language models are few-shot learners
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., and Amodei, D · 2020
Earlier work this paper cites.
UCSG-NET- unsupervised discovering of constructive solid geometry tree
Kania, K., Zieba, M., and Kajdanowicz, T · 2020
Earlier work this paper cites.
Learning transferable visual models from natural language supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., and Sutskever, I · 2021
Earlier work this paper cites.
Engineering sketch generation for computer-aided design
Willis, K. D. D., Jayaraman, P. K., Lambourne, J. G., Chu, H., and Pu, Y · 2021
Earlier work this paper cites.
Deepcad: A deep generative network for computer-aided design models
Wu, R., Xiao, C., and Zheng, C · 2021
Earlier work this paper cites.
LoRA: Low-rank adaptation of large language models
Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W · 2022
Earlier work this paper cites.
Vitruvion: A generative model of parametric CAD sketches
Seff, A., Zhou, W., Richardson, N., and Adams, R. P · 2022
Earlier work this paper cites.
Neural face identification in a 2d wireframe projection of a manifold object
Wang, K., Zheng, J., and Zhou, Z · 2022
Earlier work this paper cites.
Skexgen: Autoregressive generation of cad construction sequences with disentangled codebooks
Xu, X., Willis, K. D., Lambourne, J. G., Cheng, C.-Y., Jayaraman, P. K., and Furukawa, Y · 2022
Earlier work this paper cites.
Capri-net: Learning compact cad shapes with adaptive primitive assembly
Yu, F., Chen, Z., Li, M., Sanghi, A., Shayani, H., Mahdavi-Amiri, A., and Zhang, H · 2022
Earlier work this paper cites.
Sparks of artificial general intelligence: Early experiments with gpt-4
Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y. T., Li, Y., Lundberg, S., Nori, H., Palangi, H., Ribeiro, M. T., and Zhang, Y · 2023
Earlier work this paper cites.
What Sets Proficient and Expert Users Apart? Results of a Computer-Aided Design Experiment
Deng, Y., Chen, J., and Olechowski, A · 2023
Cited alongside, same era.
Solidgen: An autoregressive model for direct b-rep synthesis
Jayaraman, P. K., Lambourne, J. G., Desai, N., Willis, K., Sanghi, A., and Morris, N. J. W · 2023
Cited alongside, same era.
G-eval: NLG evaluation using gpt-4 with better human alignment
Liu, Y., Iter, D., Xu, Y., Wang, S., Xu, R., and Zhu, C · 2023
Cited alongside, same era.
How can large language models help humans in design and manufacturing?
Makatura, L., Foshey, M., Wang, B., HähnLein, F., Ma, P., Deng, B., Tjandrasuwita, M., Spielberg, A., Owens, C. E., Chen, P. Y., et al · 2023
Cited alongside, same era.
Llama: Open and efficient foundation language models, 2023
Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., Rodriguez, A., Joulin, A., Grave, E., and Lample, G · 2023
Rich human feedback for text-to-image generation
Liang, Y., He, J., Li, G., Li, P., Klimovskiy, A., Carolan, N., Sun, J., Pont-Tuset, J., Young, S., Yang, F., Ke, J., Dvijotham, K. D., Collins, K. M., Luo, Y., Li, Y., Kohlhoff, K. J., Ramachandran, D., and Navalpakkam, V · 2024
Later among the works it cites.
Provably mitigating overoptimization in rlhf: Your sft loss is implicitly an adversarial regularizer
Liu, Z., Lu, M., Zhang, S., Liu, B., Guo, H., Yang, Y., Blanchet, J., and Wang, Z · 2024
Later among the works it cites.
Draw step by step: Reconstructing cad construction sequences from point clouds via multimodal diffusion
Ma, W., Chen, S., Lou, Y., Li, X., and Zhou, X · 2024
Later among the works it cites.
The llama 3 herd of models, 2024
Meta · 2024
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OpenAI · 2024
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Cited alongside, same era.
Hierarchical neural coding for controllable cad model generation
Xu, X., Jayaraman, P. K., Lambourne, J. G., Willis, K. D., and Furukawa, Y · 2023
Cited alongside, same era.
A Survey of Large Language Models, May 2023
Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., Du, Y., Yang, C., Chen, Y., Chen, Z., Jiang, J., Ren, R., Li, Y., Tang, X., Liu, Z., Liu, P., Nie, J.-Y., and Wen, J.-R · 2023
Cited alongside, same era.
Knowledge-to-SQL: Enhancing SQL generation with data expert LLM
Hong, Z., Yuan, Z., Chen, H., Zhang, Q., Huang, F., and Huang, X · 2024
Cited alongside, same era.
A survey of reinforcement learning from human feedback, 2024
Kaufmann, T., Weng, P., Bengs, V., and Hüllermeier, E · 2024
Cited alongside, same era.
RLAIF vs. RLHF: scaling reinforcement learning from human feedback with AI feedback
Lee, H., Phatale, S., Mansoor, H., Mesnard, T., Ferret, J., Lu, K., Bishop, C., Hall, E., Carbune, V., Rastogi, A., and Prakash, S · 2024
Cited alongside, same era.
CAD translator: An effective drive for text to 3d parametric computer-aided design generative modeling
Li, X., Song, Y., Lou, Y., and Zhou, X · 2024
Cited alongside, same era.
Cad-signet: Cad language inference from point clouds using layer-wise sketch instance guided attention
Khan, M. S., Dupont, E., Ali, S. A., Cherenkova, K., Kacem, A., and Aouada, D
Cited in the paper.
Direct preference optimization: Your language model is secretly a reward model, 2024
Rafailov, R., Sharma, A., Mitchell, E., Ermon, S., Manning, C. D., and Finn, C · 2024
Later among the works it cites.
Boosting text-to-video generative model with mllms feedback
Wu, X., Huang, S., Wang, G., Xiong, J., and Wei, F · 2024
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Brepgen: A b-rep generative diffusion model with structured latent geometry
Xu, X., Lambourne, J., Jayaraman, P., Wang, Z., Willis, K., and Furukawa, Y · 2024
Later among the works it cites.
D 2 CSG: Unsupervised learning of compact csg trees with dual complements and dropouts
Yu, F., Chen, Q., Tanveer, M., Mahdavi Amiri, A., and Zhang, H · 2024
Later among the works it cites.
Longreward: Improving long-context large language models with ai feedback, 2024
Zhang, J., Hou, Z., Lv, X., Cao, S., Hou, Z., Niu, Y., Hou, L., Dong, Y., Feng, L., and Li, J · 2024
Later among the works it cites.
Flexcad: Unified and versatile controllable CAD generation with fine-tuned large language models
Zhang, Z., Sun, S., Wang, W., Cai, D., and Bian, J · 2025
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