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Updated: Jul 24, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
One hundred important questions facing plant science derived using a large language model
Evgenios Agathokleous1, Matthias C Rillig2, Josep Peñuelas3
1Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China.
Abstract:
Artificial intelligence (AI) is advancing rapidly and continually evolving in various fields. Recently, the release of ChatGPT has sparked significant public interest. In this study, we revisit the '100 Important Questions Facing Plant Science' by leveraging ChatGPT as a valuable tool for generating thought-provoking questions relevant to plant science. These questions primarily revolve around the utilization of plants in product development, understanding plant mechanisms, plant-environment interactions, and enhancing plant traits, with an emphasis on sustainable product development. While ChatGPT may not capture certain crucial aspects highlighted by scientists, it offers valuable insights into the questions generated by experts. Our analysis demonstrates that ChatGPT can be cautiously employed as a supportive tool to facilitate, streamline, and expedite specific tasks in plant science.
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