K-LM: Knowledge Augmenting in Language Models Within the Scholarly Domain
Author:
Affiliation:
1. Department of Mathematics and Computer Science, University of Cagliari, Cagliari, Italy
2. Philips Research, High Tech Campus, Eindhoven, The Netherlands
Funder
European Unions’s Horizon 2020 Marie Sklodowska-Curie Industrial Training Network Program—PhilHumans
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09866735.pdf?arnumber=9866735
Reference47 articles.
1. Anatomy of Preprocessing of Big Data for Monolingual Corpora Paraphrase Extraction: Source Language Sentence Selection
2. Ensembling Classical Machine Learning and Deep Learning Approaches for Morbidity Identification From Clinical Notes
3. Learning beyond datasets: Knowledge graph augmented neural networks for natural language processing;annervaz;Proc Conf North Amer Chapter Assoc Comput Linguistics Hum Lang Technol (Long Papers),2018
4. K-BERT: Enabling Language Representation with Knowledge Graph
5. You can teach an old dog new tricks! on training knowledge graph embeddings;ruffinelli;Proc Int Conf Learn Represent,2019
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