Future-proofing geotechnics workflows: accelerating problem-solving with large language models

Wu, Stephen; Otake, Yu; Mizutani, Daijiro; Liu, Chang; Asano, Kotaro; Sato, Nana; Saito, Taiga; Baba, Hidetoshi; Fukunaga, Yusuke; Higo, Yosuke; Kamura, Akiyoshi; Kodama, Shinnosuke; Metoki, Masataka; Nakamura, Tomoka; Nakazato, Yuto; Shioi, Akihiro; Takenobu, Masahiro; Tsukioka, Keigo; Yoshikawa, Ryo

doi:10.1080/17499518.2024.2381026

Georisk: Assessment and Management of Risk for Engineered Syste

2024

DOI: 10.1080/17499518.2024.2381026

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Future-proofing geotechnics workflows: accelerating problem-solving with large language models

Stephen Wu,

Yu Otake,

Daijiro Mizutani

et al.

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GeoLLM: A specialized large language model framework for intelligent geotechnical design

Xu,

Zhang,

Yin

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Computers and Geotechnics

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GeoLLM: A specialized large language model framework for intelligent geotechnical design

Xu,

Zhang,

Yin

et al. 2025

Computers and Geotechnics

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Report for ISSMGE TC309/TC304/TC222 and ASCE Geo-Institute Risk Assessment and Management Committee Fourth Machine Learning in Geotechnics Dialogue on “Machine Learning Supremacy Projects”

Leung,

Phoon,

Xiao

et al. 2024

Georisk: Assessment and Management of Risk for Engineered Syste

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Future of Machine Learning in Geotechnics (FOMLIG), 5–6 Dec 2023, Okayama, Japan

Phoon,

Shuku

2024

Georisk: Assessment and Management of Risk for Engineered Syste

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Future-proofing geotechnics workflows: accelerating problem-solving with large language models

Cited by 3 publications

References 30 publications

GeoLLM: A specialized large language model framework for intelligent geotechnical design

GeoLLM: A specialized large language model framework for intelligent geotechnical design

Report for ISSMGE TC309/TC304/TC222 and ASCE Geo-Institute Risk Assessment and Management Committee Fourth Machine Learning in Geotechnics Dialogue on “Machine Learning Supremacy Projects”

Future of Machine Learning in Geotechnics (FOMLIG), 5–6 Dec 2023, Okayama, Japan

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