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Graphics design is important for various applications, including movie production and game design.
Liu, J., Gan, Y., Dong, J., Qi, L., Sun, X., Jian, M., Wang, L., Yu, H.: Perception-driven procedural texture generation from examples. Neurocomputing 291
2018
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2018
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Shi, L., Li, B., Hašan, M., Sunkavalli, K., Boubekeur, T., Mech, R., Matusik, W.: Match: Differentiable material graphs for procedural material capture. ACM Transactions on Graphics (TOG) 39
2020
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Shimizu, E., Fisher, M., Paris, S., McCann, J., Fatahalian, K.: Design adjectives: A framework for interactive model-guided exploration of parameterized design spaces. In: Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology. pp. 261–278 (2020)
2020
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2021
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Chen, M., Tworek, J., Jun, H., Yuan, Q., de Oliveira Pinto, H.P., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., Brockman, G., Ray, A., Puri, R., Krueger, G., Petrov, M., Khlaaf, H., Sastry, G., Mishkin, P., Chan, B., Gray, S., Ryder, N., Pavlov, M., Power, A., Kaiser, L., Bavarian, M., Winter, C., Tillet, P., Such, F.P., Cummings, D., Plappert, M., Chantzis, F., Barnes, E., Herbert-Voss, A., Guss, W.H., Nichol, A., Paino, A., Tezak, N., Tang, J., Babuschkin, I., Balaji, S., Jain, S., Saunders, W., Hesse, C., Carr, A.N., Leike, J., Achiam, J., Misra, V., Morikawa, E., Radford, A., Knight, M., Brundage, M., Murati, M., Mayer, K., Welinder, P., McGrew, B., Amodei, D., McCandlish, S., Sutskever, I., Zaremba, W.: Evaluating large language models trained on code (2021)
2021
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2021
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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
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2022
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Chen, Y., Chen, R., Lei, J., Zhang, Y., Jia, K.: Tango: Text-driven photorealistic and robust 3d stylization via lighting decomposition. Advances in Neural Information Processing Systems 35
2022
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2022
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Hu, Y., Guerrero, P., Hasan, M., Rushmeier, H., Deschaintre, V.: Node graph optimization using differentiable proxies. In: ACM SIGGRAPH 2022 conference proceedings. pp. 1–9 (2022)
2022
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Hu, Y., He, C., Deschaintre, V., Dorsey, J., Rushmeier, H.: An inverse procedural modeling pipeline for svbrdf maps. ACM Transactions on Graphics (TOG) 41
2022
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Tchapmi, L.P., Ray, T., Tchapmi, M., Shen, B., Martin-Martin, R., Savarese, S.: Generating procedural 3d materials from images using neural networks. In: 2022 4th International Conference on Image, Video and Signal Processing. pp. 32–40 (2022)
2022
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Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., Le, Q.V., Zhou, D., et al.: Chain-of-thought prompting elicits reasoning in large language models. Advances in Neural Information Processing Systems 35
2022
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2023
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Betker, J., Goh, G., Jing, L., Brooks, T., Wang, J., Li, L., Ouyang, L., Zhuang, J., Lee, J., Guo, Y., et al.: Improving image generation with better captions. Computer Science. https://cdn. openai. com/papers/dall-e-3. pdf 2
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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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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
Cited alongside, same era.
2023
Cited alongside, same era.
Liang, J., Huang, W., Xia, F., Xu, P., Hausman, K., Ichter, B., Florence, P., Zeng, A.: Code as policies: Language model programs for embodied control. In: 2023 IEEE International Conference on Robotics and Automation (ICRA). pp. 9493–9500. IEEE (2023)
2023
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Olausson, T.X., Inala, J.P., Wang, C., Gao, J., Solar-Lezama, A.: Is self-repair a silver bullet for code generation? In: The Twelfth International Conference on Learning Representations (2023)
2023
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OpenAI: Gpt-4 system card. OpenAI (2023), https://cdn.openai.com/papers/gpt-4-system-card.pdf
2023
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OpenAI: Gpt-4v(ision) system card. OpenAI (2023), https://api.semanticscholar.org/CorpusID:263218031
2023
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Park, J.S., O’Brien, J., Cai, C.J., Morris, M.R., Liang, P., Bernstein, M.S.: Generative agents: Interactive simulacra of human behavior. In: Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. pp. 1–22 (2023)
2023
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2023
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2023
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2023
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Yang, H., Chen, Y., Pan, Y., Yao, T., Chen, Z., Mei, T.: 3dstyle-diffusion: Pursuing fine-grained text-driven 3d stylization with 2d diffusion models. In: Proceedings of the 31st ACM International Conference on Multimedia. pp. 6860–6868 (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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Li, C., Wong, C., Zhang, S., Usuyama, N., Liu, H., Yang, J., Naumann, T., Poon, H., Gao, J.: Llava-med: Training a large language-and-vision assistant for biomedicine in one day. Advances in Neural Information Processing Systems 36
2024
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Romera-Paredes, B., Barekatain, M., Novikov, A., Balog, M., Kumar, M.P., Dupont, E., Ruiz, F.J., Ellenberg, J.S., Wang, P., Fawzi, O., et al.: Mathematical discoveries from program search with large language models. Nature 625
2024
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Schick, T., Dwivedi-Yu, J., Dessì, R., Raileanu, R., Lomeli, M., Hambro, E., Zettlemoyer, L., Cancedda, N., Scialom, T.: Toolformer: Language models can teach themselves to use tools. Advances in Neural Information Processing Systems 36
2024
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2024
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Yang, Y., Sun, F.Y., Weihs, L., VanderBilt, E., Herrasti, A., Han, W., Wu, J., Haber, N., Krishna, R., Liu, L., et al.: Holodeck: Language guided generation of 3d embodied ai environments. In: The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024). vol. 30, pp. 20–25. IEEE/CVF (2024)
2024
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Yao, S., Yu, D., Zhao, J., Shafran, I., Griffiths, T., Cao, Y., Narasimhan, K.: Tree of thoughts: Deliberate problem solving with large language models. Advances in Neural Information Processing Systems 36
2024
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