Cai, T. (2024). Large language models as tool makers. Artificial Intelligence, 325, 103481. https://doi.org/10.1016/j.artint.2023.103481
Chaillou, S. (2022). Artificial intelligence and architecture: From research to practice. Architectural Design, 92(1), 76–83. https://doi.org/10.1002/ad.2785
Du, C., Nousias, S., & Borrmann, A. (2024). Towards a copilot in BIM authoring tool using large language model based agent for intelligent human-machine interaction. Automation in Construction, 156, 105124. https://doi.org/10.1016/j.autcon.2023.105124
Jain, N., Chiang, P. Y., Wen, Y., Kirchenbauer, J., Chu, H. M., Somepalli, G., ... & Goldstein, T. (2023). Neftune: Noisy embeddings improve instruction finetuning. arXiv preprint arXiv:2310.05914.
Jiang, C., Zheng, Z., Liang, X., Lin, J. R., Ma, Z., & Lu, X. Z. (2024). A new interaction paradigm for architectural design driven by large language model. Automation in Construction, 158, 105216. https://doi.org/10.1016/j.autcon.2023.105216
Li, C., Zhang, T., Du, X., Zhang, Y., & Xie, H. (2024). Generative AI for architectural design: A literature review. Buildings, 14(2), 361. https://doi.org/10.3390/buildings14020361
Parthasarathy, V. B., Zafar, A., Khan, A., & Shahid, A. (2024). The ultimate guide to fine-tuning LLMs from basics to breakthroughs: An exhaustive review of technologies, research, best practices, applied research challenges and opportunities. arXiv preprint, arXiv:2408.13296. https://arxiv.org/abs/2408.13296
Qin, Y. (2023). Tool learning with foundation models. Journal of Artificial Intelligence Research, 78, 1449–1459. https://doi.org/10.1613/jair.1.14564
Talkhounche, S. N. (2024). A natural language interface for modeling in Rhino 3D using large language models. Computer-Aided Design and Applications, 21(4), 723–741. https://doi.org/10.14733/cadaps.2024.723-741
Zhang, B., Liu, Z., Cherry, C., & Firat, O. (2024). When scaling meets llm finetuning: The effect of data, model and finetuning method. arXiv preprint arXiv:2402.17193.
Zhang, Y., & Wallace, B. (2015). A sensitivity analysis of (and practitioners' guide to) convolutional neural networks for sentence classification. arXiv preprint, arXiv:1510.03820. https://arxiv.org/abs/1510.03820