2020
SEMEVAL
SemEval 2020
IITK at SemEval-2020 Task 10: Transformers for Emphasis Selection
Abstract
AbstractWe propose an end-to-end model that takes as input the text and corresponding to each word gives the probability of the word to be emphasized. Our results show that transformer-based models are particularly effective in this task. We achieved an evaluation score of 0.810 and were ranked third on the leaderboard.
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Interdisciplinary Bridge
β Deep Learning and Machine Learning
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Cross-Pollinator
β Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio