id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-119104-9d421si9	Huynh, Tin Van	BANANA at WNUT-2020 Task 2: Identifying COVID-19 Information on Twitter by Combining Deep Learning and Transfer Learning Models	2020-09-06		.txt	text/plain	1816	134	63	title: BANANA at WNUT-2020 Task 2: Identifying COVID-19 Information on Twitter by Combining Deep Learning and Transfer Learning Models In this article, we present our approach at WNUT-2020 Task 2 to identify Tweets containing information about COVID-19 on the social networking platform Twitter or not. • Firstly, we implemented four different models based on neural networks and transformers such as Bi-GRU-CNN, BERT, RoBERTa, XLNet to solve the WNUT-2020 Task 2: Identification of informative COVID-19 English Tweets. In this paper, we propose an ensemble method that combines the deep learning models with the transfer learning models to identify information about COVID-19 from users' tweets. In this paper, we used the SOTA transfer learning models, such as BERT (Devlin et al., 2019) , RoBERTa (Liu et al., 2019) , and XLNet (Yang et al., 2019) with fine-tuning techniques for the problem of identifying informative tweet about COVID-19.	./cache/cord-119104-9d421si9.txt	./txt/cord-119104-9d421si9.txt