@inproceedings{nguyen-etal-2025-climate,
title = "My Climate {C}o{P}ilot: A Question Answering System for Climate Adaptation in Agriculture",
author = "Nguyen, Vincent and
Hallgren, Willow and
Harkin, Ashley and
Prakash, Mahesh and
Karimi, Sarvnaz",
editor = "Mishra, Pushkar and
Muresan, Smaranda and
Yu, Tao",
booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.acl-demo.7/",
doi = "10.18653/v1/2025.acl-demo.7",
pages = "62--70",
ISBN = "979-8-89176-253-4",
abstract = "Accurately answering climate science questions requires scientific literature and climate data. Interpreting climate literature and data, however, presents inherent challenges such as determining relevant climate factors and drivers, interpreting uncertainties in the science and data, and dealing with the sheer volume of data. My Climate CoPilot is a platform that assists a range of potential users, such as farmer advisors, to mitigate and adapt to projected climate changes by providing answers to questions that are grounded in evidence. It emphasises transparency, user privacy, low-resource use, and provides automatic evaluation. It also strives for scientific robustness and accountability. Fifty domain experts carefully evaluated every aspect of My Climate CoPilot and based on their interactions and feedback, the system continues to evolve."
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<abstract>Accurately answering climate science questions requires scientific literature and climate data. Interpreting climate literature and data, however, presents inherent challenges such as determining relevant climate factors and drivers, interpreting uncertainties in the science and data, and dealing with the sheer volume of data. My Climate CoPilot is a platform that assists a range of potential users, such as farmer advisors, to mitigate and adapt to projected climate changes by providing answers to questions that are grounded in evidence. It emphasises transparency, user privacy, low-resource use, and provides automatic evaluation. It also strives for scientific robustness and accountability. Fifty domain experts carefully evaluated every aspect of My Climate CoPilot and based on their interactions and feedback, the system continues to evolve.</abstract>
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%0 Conference Proceedings
%T My Climate CoPilot: A Question Answering System for Climate Adaptation in Agriculture
%A Nguyen, Vincent
%A Hallgren, Willow
%A Harkin, Ashley
%A Prakash, Mahesh
%A Karimi, Sarvnaz
%Y Mishra, Pushkar
%Y Muresan, Smaranda
%Y Yu, Tao
%S Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-253-4
%F nguyen-etal-2025-climate
%X Accurately answering climate science questions requires scientific literature and climate data. Interpreting climate literature and data, however, presents inherent challenges such as determining relevant climate factors and drivers, interpreting uncertainties in the science and data, and dealing with the sheer volume of data. My Climate CoPilot is a platform that assists a range of potential users, such as farmer advisors, to mitigate and adapt to projected climate changes by providing answers to questions that are grounded in evidence. It emphasises transparency, user privacy, low-resource use, and provides automatic evaluation. It also strives for scientific robustness and accountability. Fifty domain experts carefully evaluated every aspect of My Climate CoPilot and based on their interactions and feedback, the system continues to evolve.
%R 10.18653/v1/2025.acl-demo.7
%U https://aclanthology.org/2025.acl-demo.7/
%U https://doi.org/10.18653/v1/2025.acl-demo.7
%P 62-70
Markdown (Informal)
[My Climate CoPilot: A Question Answering System for Climate Adaptation in Agriculture](https://aclanthology.org/2025.acl-demo.7/) (Nguyen et al., ACL 2025)
ACL