@inproceedings{davletov-etal-2021-liori-semeval,
title = "{LIORI} at {S}em{E}val-2021 Task 8: Ask Transformer for measurements",
author = "Davletov, Adis and
Gordeev, Denis and
Arefyev, Nikolay and
Davletov, Emil",
editor = "Palmer, Alexis and
Schneider, Nathan and
Schluter, Natalie and
Emerson, Guy and
Herbelot, Aurelie and
Zhu, Xiaodan",
booktitle = "Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.semeval-1.178/",
doi = "10.18653/v1/2021.semeval-1.178",
pages = "1249--1254",
abstract = "This work describes our approach for subtasks of SemEval-2021 Task 8: MeasEval: Counts and Measurements which took the official first place in the competition. To solve all subtasks we use multi-task learning in a question-answering-like manner. We also use learnable scalar weights to weight subtasks' contribution to the final loss in multi-task training. We fine-tune LUKE to extract quantity spans and we fine-tune RoBERTa to extract everything related to found quantities, including quantities themselves."
}
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<abstract>This work describes our approach for subtasks of SemEval-2021 Task 8: MeasEval: Counts and Measurements which took the official first place in the competition. To solve all subtasks we use multi-task learning in a question-answering-like manner. We also use learnable scalar weights to weight subtasks’ contribution to the final loss in multi-task training. We fine-tune LUKE to extract quantity spans and we fine-tune RoBERTa to extract everything related to found quantities, including quantities themselves.</abstract>
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%0 Conference Proceedings
%T LIORI at SemEval-2021 Task 8: Ask Transformer for measurements
%A Davletov, Adis
%A Gordeev, Denis
%A Arefyev, Nikolay
%A Davletov, Emil
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Schluter, Natalie
%Y Emerson, Guy
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%S Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F davletov-etal-2021-liori-semeval
%X This work describes our approach for subtasks of SemEval-2021 Task 8: MeasEval: Counts and Measurements which took the official first place in the competition. To solve all subtasks we use multi-task learning in a question-answering-like manner. We also use learnable scalar weights to weight subtasks’ contribution to the final loss in multi-task training. We fine-tune LUKE to extract quantity spans and we fine-tune RoBERTa to extract everything related to found quantities, including quantities themselves.
%R 10.18653/v1/2021.semeval-1.178
%U https://aclanthology.org/2021.semeval-1.178/
%U https://doi.org/10.18653/v1/2021.semeval-1.178
%P 1249-1254
Markdown (Informal)
[LIORI at SemEval-2021 Task 8: Ask Transformer for measurements](https://aclanthology.org/2021.semeval-1.178/) (Davletov et al., SemEval 2021)
ACL