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Exploring Pre-Trained Language Models to Build Knowledge Gr..:

, In: 2022 IEEE International Conference on Big Data (Big Data),

An, Yuan ; Greenberg, Jane ; Hu, Xiaohua... - p. 3651-3658 , 2022

Link: https://doi.org/10.1109/BigData55660.2022.10020568

RT 
T1 <cTitle>2022 IEEE International Conference on Big Data (Big Data)</cTitle>: T1 <Title>Exploring Pre-Trained Language Models to Build Knowledge Graph for Metal-Organic Frameworks (MOFs)</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10020568&Exemplar=1&LAN=DE
				
A1 An, Yuan
A1 Greenberg, Jane
A1 Hu, Xiaohua
A1 Kalinowski, Alex
A1 Fang, Xiao
A1 Zhao, Xintong
A1 McCLellan, Scott
A1 Uribe-Romo, Fernando J.
A1 Langlois, Kyle
A1 Furst, Jacob
A1 Gomez-Gualdron, Diego A.
A1 Fajardo-Rojas, Fernando
A1 Ardila, Katherine
A1 Saikin, Semion K.
A1 Harper, Corey A.
A1 Daniel, Ron
YR 2022
K1 Materials science and technology
K1 Big Data
K1 Benchmark testing
K1 Natural language processing
K1 Data models
K1 Artificial intelligence
K1 Domain specific languages
K1 Knowledge Graph
K1 Pre-trained Language Model
K1 Prompt Probing
K1 Materials Science
K1 Metal-Organic Frameworks
SP 3651
OP 3658
LK http://dx.doi.org/https://doi.org/10.1109/BigData55660.2022.10020568
DO https://doi.org/10.1109/BigData55660.2022.10020568
SF ELIB - SuUB Bremen

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