{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T02:15:48Z","timestamp":1783995348927,"version":"3.55.0"},"reference-count":82,"publisher":"American Society of Civil Engineers (ASCE)","issue":"4","content-domain":{"domain":["ascelibrary.org"],"crossmark-restriction":true},"short-container-title":["J. Comput. Civ. Eng."],"published-print":{"date-parts":[[2025,7]]},"DOI":"10.1061\/jccee5.cpeng-6037","type":"journal-article","created":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T09:55:18Z","timestamp":1746611718000},"update-policy":"https:\/\/doi.org\/10.1061\/do.news.20190416.0001","source":"Crossref","is-referenced-by-count":16,"title":["The Framework and Implementation of Using Large Language Models to Answer Questions about Building Codes and Standards"],"prefix":"10.1061","volume":"39","author":[{"given":"Isaac","family":"Joffe","sequence":"first","affiliation":[{"name":"Univ. of Alberta","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6217-2772","authenticated-orcid":true,"given":"George","family":"Felobes","sequence":"additional","affiliation":[{"name":"Univ. of Alberta","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youssef","family":"Elgouhari","sequence":"additional","affiliation":[{"name":"Univ. of Alberta","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Talebi Kalaleh","sequence":"additional","affiliation":[{"name":"Univ. of Alberta","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1409-3562","authenticated-orcid":true,"given":"Qipei","family":"Mei","sequence":"additional","affiliation":[{"name":"Univ. of Alberta","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying Hei","family":"Chui","sequence":"additional","affiliation":[{"name":"Univ. of Alberta","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"30","reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.37284\/eaje.6.1.1272"},{"key":"e_1_3_3_3_1","unstructured":"Anil R. et al. 2023. \u201cPaLM 2 technical report.\u201d Preprint submitted May 17 2023. https:\/\/arxiv.org\/abs\/2305.10403."},{"key":"e_1_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.02.029"},{"key":"e_1_3_3_5_1","unstructured":"Bommasani R. et al. 2022. \u201cOn the opportunities and risks of foundation models.\u201d Preprint submitted August 16 2021. https:\/\/arxiv.org\/abs\/2108.07258."},{"key":"e_1_3_3_6_1","unstructured":"Brown T. B. et al. 2020. \u201cLanguage models are few-shot learners.\u201d In Proc. 34th Int. Conf. on Neural Information Processing Systems NIPS \u201920. Red Hook NY: Curran Associates."},{"key":"e_1_3_3_7_1","volume-title":"National building code of Canada: 2020","author":"Canadian Commission on Building and Fire Codes","year":"2022","unstructured":"Canadian Commission on Building and Fire Codes. 2022. National building code of Canada: 2020. Ottawa: National Research Council of Canada."},{"key":"e_1_3_3_8_1","unstructured":"Chen B. Z. Zhang N. Langren\u00e9 and S. Zhu. 2023a. \u201cUnleashing the potential of prompt engineering in large language models: A comprehensive review.\u201d Preprint submitted October 23 2023. https:\/\/arxiv.org\/abs\/2310.14735."},{"key":"e_1_3_3_9_1","doi-asserted-by":"crossref","unstructured":"Chen D. A. Fisch J. Weston and A. Bordes. 2017. \u201cReading wikipedia to answer open-domain questions.\u201d In Vol. 1 of Proc. 55th Annual Meeting of the Association for Computational Linguistics edited by R. Barzilay and M.-Y. Kan 1870\u20131879. Toronto: Association for Computational Linguistics.","DOI":"10.18653\/v1\/P17-1171"},{"key":"e_1_3_3_10_1","doi-asserted-by":"crossref","unstructured":"Chen W. P. Verga M. de Jong J. Wieting and W. Cohen. 2023b. \u201cAugmenting pre-trained language models with QA-memory for open-domain question answering.\u201d In Proc. 17th Conf. of the European Chapter of the Association for Computational Linguistics edited by A. Vlachos and I. Augenstein 1597\u20131610. Dubrovnik Croatia: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2023.eacl-main.117"},{"key":"e_1_3_3_11_1","volume-title":"Building codes illustrated: A guide to understanding the 2021 international building code","author":"Ching F.","year":"2021","unstructured":"Ching, F., and S. Winkel. 2021. Building codes illustrated: A guide to understanding the 2021 international building code. New York: Wiley."},{"key":"e_1_3_3_12_1","first-page":"1","article-title":"PaLM: Scaling language modeling with pathways","volume":"24","author":"Chowdhery A.","year":"2023","unstructured":"Chowdhery, A., et al. 2023. \u201cPaLM: Scaling language modeling with pathways.\u201d J. Mach. Learn. Res. 24: 1\u2013113.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_3_13_1","unstructured":"Clark P. et al. 2018. \u201cThink you have solved question answering? Try ARC the AI2 reasoning challenge.\u201d Preprint submitted March 14 2018. https:\/\/arxiv.org\/abs\/1803.05457."},{"key":"e_1_3_3_14_1","unstructured":"Dai A. M. C. Olah and Q. V. Le. 2015. \u201cDocument embedding with paragraph vectors.\u201d Preprint submitted July 29 2015. https:\/\/arxiv.org\/abs\/1507.07998."},{"key":"e_1_3_3_15_1","unstructured":"Devlin J. M.-W. Chang K. Lee and K. Toutanova. 2019. \u201cBERT: Pre-training of deep bidirectional transformers for language understanding.\u201d In Vol. 1 of Proc. 2019 Conf. of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies edited by J. Burstein C. Doran and T. Solorio 4171\u20134186. Minneapolis: Association for Computational Linguistics."},{"key":"e_1_3_3_16_1","doi-asserted-by":"crossref","unstructured":"Douka S. H. Abdine M. Vazirgiannis R. El Hamdani and D. Restrepo Amariles. 2022. \u201cJuriBERT: A masked-language model adaptation for French legal text.\u201d In Proc. Natural Legal Language Processing Workshop 2021 edited by N. Aletras I. Androutsopoulos L. Barrett C. Goanta and D. Preotiuc-Pietro 95\u2013101. Punta Cana Dominican Republic: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2021.nllp-1.9"},{"key":"e_1_3_3_17_1","doi-asserted-by":"crossref","unstructured":"Fabbri A. P. Ng Z. Wang R. Nallapati and B. Xiang. 2020. \u201cTemplate-based question generation from retrieved sentences for improved unsupervised question answering.\u201d In Proc. 58th Annual Meeting of the Association for Computational Linguistics edited by D. Jurafsky J. Chai N. Schluter and J. Tetreault 4508\u20134513. Toronto: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2020.acl-main.413"},{"key":"e_1_3_3_18_1","unstructured":"Feldman P. J. R. Foulds and S. Pan. 2023. \u201cTrapping LLM hallucinations using tagged context prompts.\u201d Preprint submitted June 9 2023. https:\/\/arxiv.org\/abs\/2306.06085."},{"key":"e_1_3_3_19_1","unstructured":"Fuchs S. and R. Amor. 2021. \u201cNatural language processing for building code interpretation: A systematic review.\u201d In Proc. 38th Int. Conf. of CIB W78 291\u2013303. Delft Netherlands: International Council for Research and Innovation in Buildings and Construction."},{"key":"e_1_3_3_20_1","volume-title":"A framework for few-shot language model evaluation","author":"Gao L.","year":"2021","unstructured":"Gao, L., et al. 2021. A framework for few-shot language model evaluation. Geneva: Zenodo. https:\/\/doi.org\/10.5281\/zenodo.12608602."},{"key":"e_1_3_3_21_1","unstructured":"Gao Y. Y. Xiong X. Gao K. Jia J. Pan Y. Bi Y. Dai J. Sun M. Wang and H. Wang. 2024. \u201cRetrieval-augmented generation for large language models: A survey.\u201d Preprint submitted December 18 2023. https:\/\/arxiv.org\/abs\/2312.10997."},{"key":"e_1_3_3_22_1","doi-asserted-by":"publisher","DOI":"10.1002\/int.22955"},{"key":"e_1_3_3_23_1","unstructured":"Guo Z. et al. 2023. \u201cEvaluating large language models: A comprehensive survey.\u201d Preprint submitted October 30 2023. https:\/\/arxiv.org\/abs\/2310.19736."},{"key":"e_1_3_3_24_1","unstructured":"Guu K. K. Lee Z. Tung P. Pasupat and M. Chang. 2020. \u201cRetrieval augmented language model pre-training.\u201d Preprint submitted February 10 2020. https:\/\/arxiv.org\/abs\/2002.08909."},{"key":"e_1_3_3_25_1","doi-asserted-by":"publisher","DOI":"10.1002\/ev.20556"},{"key":"e_1_3_3_26_1","unstructured":"Hendrycks D. et al. 2021. \u201cMeasuring massive multitask language understanding.\u201d Preprint submitted September 7 2020. https:\/\/arxiv.org\/abs\/2009.03300."},{"key":"e_1_3_3_27_1","unstructured":"Hoffmann J. et al. 2022. \u201cTraining compute-optimal large language models.\u201d In Proc. 36th Int. Conf. on Neural Information Processing Systems. Red Hook NY: Curran Associates."},{"key":"e_1_3_3_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122666"},{"key":"e_1_3_3_29_1","doi-asserted-by":"crossref","unstructured":"Jiang J. K. Zhou Z. Dong K. Ye W. X. Zhao and J.-R. Wen. 2023. \u201cStructGPT: A general framework for large language model to reason over structured data.\u201d In Proc. 2023 Conf. on Empirical Methods in Natural Language Processing edited by H. Bouamor J. Pino and K. Bali 9237\u20139251. Singapore: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2023.emnlp-main.574"},{"issue":"1","key":"e_1_3_3_30_1","article-title":"Combining bim and ontology to facilitate intelligent green building evaluation","volume":"33","author":"Jiang S.","year":"2019","unstructured":"Jiang, S., N. Wang, and J. Wu. 2019. \u201cCombining bim and ontology to facilitate intelligent green building evaluation.\u201d J. Comput. Civ. Eng. 33 (1): 04018069. https:\/\/doi.org\/10.1061\/(ASCE)CP.1943-5487.0000786.","journal-title":"J. Comput. Civ. Eng."},{"key":"e_1_3_3_31_1","first-page":"962","article-title":"How can we know when language models know? on the calibration of language models for question answering","volume":"9","author":"Jiang Z.","year":"2021","unstructured":"Jiang, Z., J. Araki, H. Ding, and G. Neubig. 2021. \u201cHow can we know when language models know? on the calibration of language models for question answering.\u201d Transact. Assoc. Comput. Ling. 9 (Sep): 962\u2013977. https:\/\/doi.org\/10.1162\/tacl_a_00407.","journal-title":"Transact. Assoc. Comput. Ling."},{"key":"e_1_3_3_32_1","doi-asserted-by":"crossref","unstructured":"Kamalloo E. N. Dziri C. L. A. Clarke and D. Rafiei. 2023. \u201cEvaluating open-domain question answering in the era of large language models.\u201d In Vol. 1 of Proc. 61st Annual Meeting of the Association for Computational Linguistics edited by A. Rogers J. Boyd-Graber and N. Okazaki 5591\u20135606. Toronto: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2023.acl-long.307"},{"key":"e_1_3_3_33_1","doi-asserted-by":"crossref","unstructured":"Karpukhin V. B. Oguz S. Min P. Lewis L. Wu S. Edunov and D. Chen and W.-t. Yih. 2020. \u201cDense passage retrieval for open-domain question answering.\u201d In Proc. 2020 Conf. on Empirical Methods in Natural Language Processing (EMNLP) edited by B. Webber T. Cohn Y. He and Y. Liu 6769\u20136781. Toronto: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2020.emnlp-main.550"},{"key":"e_1_3_3_34_1","doi-asserted-by":"crossref","unstructured":"Krishna K. A. Roy and M. Iyyer. 2021. \u201cHurdles to progress in long-form question answering.\u201d In Proc. 2021 Conf. of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies edited by K. Toutanova A. Rumshisky L. Zettlemoyer D. Hakkani-Tur I. Beltagy S. Bethard R. Cotterell T. Chakraborty and Y. Zhou 4940\u20134957. Toronto: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2021.naacl-main.393"},{"key":"e_1_3_3_35_1","unstructured":"Le Q. V. and T. Mikolov. 2014. \u201cDistributed representations of sentences and documents.\u201d In Vol. 32 of Proc. 31st Int. Conf. on Machine Learning edited by E. P. Xing and T. Jebara 1188\u20131196. Beijing: Proceedings of Machine Learning Research."},{"key":"e_1_3_3_36_1","doi-asserted-by":"crossref","unstructured":"Lee K. M. W. Chang and K. Toutanova. 2019. \u201cLatent retrieval for weakly supervised open domain question answering.\u201d In Proc. 57th Annual Meeting of the Association for Computational Linguistics edited by A. Korhonen D. Traum and L. M\u2019arquez 6086\u20136096. Florence Italy: Association for Computational Linguistics.","DOI":"10.18653\/v1\/P19-1612"},{"key":"e_1_3_3_37_1","unstructured":"Liang P. et al. 2023. \u201cHolistic evaluation of language models.\u201d Preprint submitted November 16 2022. https:\/\/arxiv.org\/abs\/2211.09110."},{"key":"e_1_3_3_38_1","doi-asserted-by":"crossref","unstructured":"Lin S. J. Hilton and O. Evans. 2022. \u201cTruthfulQA: Measuring how models mimic human falsehoods.\u201d In Vol. 1 of Proc. 60th Annual Meeting of the Association for Computational Linguistics edited by S. Muresan P. Nakov and A. Villavicencio 3214\u20133252. Dublin Ireland: Proceedings of Machine Learning Research.","DOI":"10.18653\/v1\/2022.acl-long.229"},{"key":"e_1_3_3_39_1","unstructured":"Lu Y. M. Shen H. Wang X. Wang C. van Rechem T. Fu and W. Wei. 2024. \u201cMachine learning for synthetic data generation: A review.\u201d Preprint submitted February 8 2023. https:\/\/arxiv.org\/abs\/2302.04062."},{"key":"e_1_3_3_40_1","doi-asserted-by":"crossref","unstructured":"McKenna N. T. Li L. Cheng M. J. Hosseini M. Johnson and M. Steedman. 2023. \u201cSources of hallucination by large language models on inference tasks.\u201d In Proc. Findings of the Association for Computational Linguistics: EMNLP 2023 edited by H. Bouamor J. Pino and K. Bali 2758\u20132774. Singapore: Proceedings of Machine Learning Research.","DOI":"10.18653\/v1\/2023.findings-emnlp.182"},{"key":"e_1_3_3_41_1","unstructured":"Menick J. et al. 2022. \u201cTeaching language models to support answers with verified quotes.\u201d Preprint submitted March 21 2022. https:\/\/arxiv.org\/abs\/2203.11147."},{"key":"e_1_3_3_42_1","unstructured":"Mikolov T. K. Chen G. Corrado and J. Dean. 2013. \u201cEfficient estimation of word representations in vector space.\u201d In Proc. 1st Int. Conf. on Learning Representations ICLR 2013 Workshop Track Proc. Princeton NJ: NEC Laboratories America."},{"key":"e_1_3_3_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3605943"},{"key":"e_1_3_3_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2014.10.007"},{"key":"e_1_3_3_45_1","unstructured":"Myrzakhan A. S. M. Bsharat and Z. Shen. 2024. \u201cOpen LLM leaderboard: From multi-choice to open-style questions for LLMs evaluation benchmark and arena.\u201d Preprint submitted June 11 2024. https:\/\/arxiv.org\/abs\/2406.07545."},{"key":"e_1_3_3_46_1","unstructured":"Naveed H. et al. 2023. \u201cA comprehensive overview of large language models.\u201d Preprint submitted July 12 2023. https:\/\/arxiv.org\/abs\/2307.06435."},{"issue":"2","key":"e_1_3_3_47_1","article-title":"Generalized adaptive framework for computerizing the building design review process","volume":"25","author":"Nawari N. O.","year":"2019","unstructured":"Nawari, N. O. 2019. \u201cGeneralized adaptive framework for computerizing the building design review process.\u201d J. Archit. Eng. 25 (2): 04019004. https:\/\/doi.org\/10.1061\/(ASCE)AE.1943-5568.0000382.","journal-title":"J. Archit. Eng."},{"key":"e_1_3_3_48_1","unstructured":"Nikolenko S. I. 2019. \u201cSynthetic data for deep learning.\u201d Preprint submitted September 25 2019. https:\/\/arxiv.org\/abs\/1909.11512."},{"key":"e_1_3_3_49_1","unstructured":"OpenAI. 2023. \u201cGPT-4 technical report.\u201d Preprint submitted March 15 2023. https:\/\/arxiv.org\/abs\/2303.08774."},{"key":"e_1_3_3_50_1","first-page":"8024","volume-title":"Advances in neural information processing systems","author":"Paszke A.","year":"2019","unstructured":"Paszke, A., et al. 2019. \u201cPytorch: An imperative style, high-performance deep learning library.\u201d In Vol. 32 of Advances in neural information processing systems, edited by H. Wallach, H. Larochelle, A. Beygelzimer, F. d\u00b4e-Buc, E. Fox, and R. Garnett, 8024\u20138035. Red Hook, NY: Curran Associates."},{"key":"e_1_3_3_51_1","unstructured":"Penedo G. Q. Malartic D. Hesslow R. Cojocaru H. Alobeidli A. Cappelli B. Pannier E. Almazrouei and J. Launa. 2023. \u201cThe RefinedWeb dataset for Falcon LLM: Outperforming curated corpora with web data only.\u201d In Proc. 37th Int. Conf. on Neural Information Processing Systems NIPS \u201923 Red Hook NY: Curran Associates."},{"key":"e_1_3_3_52_1","unstructured":"Radford A. K. Narasimhan T. Salimans and I. Sutskever. 2018a. \u201cImproving language understanding by generative pre-training.\u201d Accessed June 11 2018. https:\/\/cdn.openai.com\/research-covers\/language-unsupervised\/language_understanding_paper.pdf."},{"key":"e_1_3_3_53_1","unstructured":"Radford A. J. Wu R. Child D. Luan D. Amodei and I. Sutskever. 2018b. \u201cLanguage models are unsupervised multitask learners.\u201d Accessed December 6 2020. https:\/\/cdn.openai.com\/better-language-models\/language_models_are_unsupervised_multitask_learners.pdf."},{"key":"e_1_3_3_54_1","doi-asserted-by":"crossref","unstructured":"Rajpurkar P. R. Jia and P. Liang. 2018. \u201cKnow what you don\u2018t know: Unanswerable questions for SQuAD.\u201d In Vol. 2 of Proc. 56th Annual Meeting of the Association for Computational Linguistics edited by I. Gurevych and Y. Miyao 784\u2013789. Melbourne VIC Australia: Association for Computational Linguistics.","DOI":"10.18653\/v1\/P18-2124"},{"key":"e_1_3_3_55_1","first-page":"1316","article-title":"In-context retrieval-augmented language models","volume":"11","author":"Ram O.","year":"2023","unstructured":"Ram, O., Y. Levine, I. Dalmedigos, D. Muhlgay, A. Shashua, K. Leyton-Brown, and Y. Shoham. 2023. \u201cIn-context retrieval-augmented language models.\u201d Trans. Assoc. Comput. Ling. 11: 1316\u20131331.","journal-title":"Trans. Assoc. Comput. Ling."},{"key":"e_1_3_3_56_1","volume-title":"Gensim\u2013python framework for vector space modelling","author":"Rehurek R.","year":"2011","unstructured":"Rehurek, R., and P. Sojka. 2011. Gensim\u2013python framework for vector space modelling. Brno, Czech Republic: Masaryk Univ."},{"key":"e_1_3_3_57_1","doi-asserted-by":"crossref","unstructured":"Risch J. T. M\u00f6ller J. Gutsch and M. Pietsch. 2021. \u201cSemantic answer similarity for evaluating question answering models.\u201d In Proc. 3rd Workshop on Machine Reading for Question Answering edited by A. Fisch A. Talmor D. Chen E. Choi M. Seo P. Lewis R. Jia and S. Min 149\u2013157. Punta Cana Dominican Republic: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2021.mrqa-1.15"},{"key":"e_1_3_3_58_1","doi-asserted-by":"publisher","DOI":"10.1002\/asi.4630270302"},{"key":"e_1_3_3_59_1","unstructured":"Sahoo P. A. K. Singh S. Saha V. Jain S. Mondal and A. Chadha. 2024. \u201cA systematic survey of prompt engineering in large language models: Techniques and applications.\u201d Preprint submitted February 5 2024. https:\/\/arxiv.org\/abs\/2402.07927."},{"key":"e_1_3_3_60_1","doi-asserted-by":"publisher","DOI":"10.1016\/0306-4573(88)90021-0"},{"key":"e_1_3_3_61_1","unstructured":"Savage N. 2023. \u201cSynthetic data could be better than real data.\u201d Accessed April 5 2025. https:\/\/www.nature.com\/articles\/d41586-023-01445-8."},{"key":"e_1_3_3_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3624724"},{"key":"e_1_3_3_63_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-024-03423-7"},{"key":"e_1_3_3_64_1","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-36271-1_24"},{"key":"e_1_3_3_65_1","unstructured":"Thoppilan R. et al. 2022. \u201cLaMDA: Language models for dialog applications.\u201d Preprint submitted January 20 2022. https:\/\/arxiv.org\/abs\/2201.08239."},{"key":"e_1_3_3_66_1","unstructured":"Touvron H. et al. 2023a. \u201cLLaMA 2: Open foundation and fine-tuned chat models.\u201d Preprint submitted July 18 2023. https:\/\/arxiv.org\/abs\/2307.09288."},{"key":"e_1_3_3_67_1","unstructured":"Touvron H. et al. 2023b. \u201cLLaMA: Open and efficient foundation language models.\u201d Preprint submitted February 27 2023. https:\/\/arxiv.org\/abs\/2302.13971."},{"key":"e_1_3_3_68_1","doi-asserted-by":"crossref","unstructured":"Trotman A. A. Puurula and B. Burgess. 2014. \u201cImprovements to BM25 and language models examined.\u201d In Proc. 19th Australasian Document Computing Symp. ADCS \u201914 58\u201365. New York: Association for Computing Machinery. https:\/\/doi.org\/10.1145\/2682862.2682863.","DOI":"10.1145\/2682862.2682863"},{"key":"e_1_3_3_69_1","volume-title":"Advances in neural information processing systems","author":"Vaswani A.","year":"2017","unstructured":"Vaswani, A., N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. u. Kaiser, and I. Polosukhin. 2017. \u201cAttention is all you need.\u201d In Vol. 30 of Advances in neural information processing systems, edited by I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett. Red Hook, NY: Curran Associates."},{"key":"e_1_3_3_70_1","doi-asserted-by":"crossref","unstructured":"Wang Y. Y. Kordi S. Mishra A. Liu N. A. Smith D. Khashabi and H. Hajishirzi. 2023. \u201cSelf-instruct: Aligning language models with self-generated instructions.\u201d In Vol. 1 of Proc. 61st Annual Meeting of the Association for Computational Linguistics edited by A. Rogers J. Boyd-Graber and N. Okazaki 13484\u201313508. Toronto: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2023.acl-long.754"},{"key":"e_1_3_3_71_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cogsys.2018.08.023"},{"key":"e_1_3_3_72_1","unstructured":"Wei J. X. Wang D. Schuurmans M. Bosma B. Ichter F. Xia E. Chi Q. Le and D. Zhou. 2023. \u201cChain-of-thought prompting elicits reasoning in large language models.\u201d Preprint submitted January 28 2022. https:\/\/arxiv.org\/abs\/2201.11903."},{"key":"e_1_3_3_73_1","unstructured":"Wolf T. et al. 2020. \u201cHuggingFace\u2019s transformers: State-of-the-art natural language processing.\u201d Preprint submitted October 9 2019. https:\/\/arxiv.org\/abs\/1910.03771."},{"key":"e_1_3_3_74_1","unstructured":"Wu C. X. Zhang Y. Zhang Y. Wang and W. Xie. 2023. \u201cPMC-LLaMA: Towards building open-source language models for medicine.\u201d Preprint submitted April 27 2023. https:\/\/arxiv.org\/abs\/2304.14454."},{"key":"e_1_3_3_75_1","doi-asserted-by":"crossref","unstructured":"Yang F. P. Zhao Z. Wang L. Wang B. Qiao J. Zhang M. Garg Q. Lin S. Rajmohan and D. Zhang. 2023a. \u201cEmpower large language model to perform better on industrial domain-specific question answering.\u201d In Proc. 2023 Conf. on Empirical Methods in Natural Language Processing: Industry Track edited by M. Wang and I. Zitouni 294\u2013312. Singapore: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2023.emnlp-industry.29"},{"key":"e_1_3_3_76_1","doi-asserted-by":"crossref","unstructured":"Yang H. X.-Y. Liu and C. D. Wang. 2023b. \u201cFinGPT: Open-source financial large language models.\u201d Preprint submitted June 9 2023. https:\/\/arxiv.org\/abs\/2306.06031.","DOI":"10.2139\/ssrn.4489826"},{"key":"e_1_3_3_77_1","doi-asserted-by":"crossref","unstructured":"Zellers R. A. Holtzman Y. Bisk A. Farhadi and Y. Choi. 2019. \u201cHellaSwag: Can a machine really finish your sentence?\u201d In Proc. 257th Annual Meeting of the Association for Computational Linguistics edited by A. Korhonen D. Traum and L. M\u2019arquez 4791\u20134800. Florence Italy: Association for Computational Linguistics.","DOI":"10.18653\/v1\/P19-1472"},{"key":"e_1_3_3_78_1","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)CP.1943-5487.0000346"},{"key":"e_1_3_3_79_1","unstructured":"Zhao W. X. et al. 2023. \u201cA survey of large language models.\u201d Preprint submitted March 31 2023. https:\/\/arxiv.org\/abs\/2303.18223."},{"key":"e_1_3_3_80_1","unstructured":"Zheng Z. K.-Y. Chen X.-Y. Cao X.-Z. Lu and J.-R. Lin. 2023. \u201cLLM-FuncMapper: Function identification for interpreting complex clauses in building codes via LLM.\u201d Preprint submitted August 17 2023. https:\/\/arxiv.org\/abs\/2308.08728."},{"key":"e_1_3_3_81_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2020.101152"},{"key":"e_1_3_3_82_1","doi-asserted-by":"crossref","unstructured":"Zhou Y. J. Lin and Z. She. 2021. \u201cAutomatic construction of building code graph for regulation intelligence.\u201d In Proc. ICCREM 2021: Proc. Int. Conf. on Construction and Real Estate Management 2021 248\u2013254. Reston VA: ASCE. https:\/\/doi.org\/10.1061\/9780784483848.028.","DOI":"10.1061\/9780784483848.028"},{"key":"e_1_3_3_83_1","unstructured":"Zhuang Y. Y. Yu K. Wang H. Sun and C. Zhang. 2023. \u201cToolQA: A dataset for LLM question answering with external tools.\u201d Preprint submitted June 23 2023. https:\/\/arxiv.org\/abs\/2306.13304."}],"container-title":["Journal of Computing in Civil Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/ascelibrary.org\/doi\/pdf\/10.1061\/JCCEE5.CPENG-6037","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T09:55:40Z","timestamp":1746611740000},"score":1,"resource":{"primary":{"URL":"https:\/\/ascelibrary.org\/doi\/10.1061\/JCCEE5.CPENG-6037"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7]]},"references-count":82,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,7]]}},"alternative-id":["10.1061\/JCCEE5.CPENG-6037"],"URL":"https:\/\/doi.org\/10.1061\/jccee5.cpeng-6037","relation":{},"ISSN":["0887-3801","1943-5487"],"issn-type":[{"value":"0887-3801","type":"print"},{"value":"1943-5487","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7]]},"assertion":[{"value":"2024-03-07","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-01-09","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-05-07","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"05025004"}}