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2021 SemEval SemEval 2021

LIORI at SemEval-2021 Task 8: Ask Transformer for measurements

Abstract

AbstractThis 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.

Authors

Adis Davletov, Denis Gordeev, Nikolay Arefyev, Emil Davletov

Topics

Artificial Intelligence > Learning Paradigms > Transfer Learning Machine Learning > Core Methods > Classification Machine Learning > Core Methods > Representation Learning Machine Learning > Learning Types > Multi-Task Learning

Keywords

multi-task learning text classification question answering named entity recognition span identification semantic extraction transformer model quantity extraction
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