TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)

December 30, 2022 ยท Declared Dead ยท ๐Ÿ› AAAI Conference on Artificial Intelligence

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Authors Rฤƒzvan-Alexandru Smฤƒdu, George-Eduard Zaharia, Andrei-Marius Avram, Dumitru-Clementin Cercel, Mihai Dascalu, Florin Pop arXiv ID 2301.06902 Category cs.CL: Computation & Language Citations 1 Venue AAAI Conference on Artificial Intelligence Last Checked 5 months ago
Abstract
Keyphrase identification and classification is a Natural Language Processing and Information Retrieval task that involves extracting relevant groups of words from a given text related to the main topic. In this work, we focus on extracting keyphrases from scientific documents. We introduce TA-DA, a Topic-Aware Domain Adaptation framework for keyphrase extraction that integrates Multi-Task Learning with Adversarial Training and Domain Adaptation. Our approach improves performance over baseline models by up to 5% in the exact match of the F1-score.
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