Bao-Tran Pham-Hong

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2020

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PGSG at SemEval-2020 Task 12: BERT-LSTM with Tweets’ Pretrained Model and Noisy Student Training Method
Bao-Tran Pham-Hong | Setu Chokshi
Proceedings of the Fourteenth Workshop on Semantic Evaluation

The paper presents a system developed for the SemEval-2020 competition Task 12 (OffensEval-2): Multilingual Offensive Language Identification in Social Media. We achieve the second place (2nd) in sub-task B: Automatic categorization of offense types and are ranked 55th with a macro F1-score of 90.59 in sub-task A: Offensive language identification. Our solution is using a stack of BERT and LSTM layers, training with the Noisy Student method. Since the tweets data contains a large number of noisy words and slang, we update the vocabulary of the BERT large model pre-trained by the Google AI Language team. We fine-tune the model with tweet sentences provided in the challenge.

2018

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Genre-Oriented Web Content Extraction with Deep Convolutional Neural Networks and Statistical Methods
Bao-Dai Nguyen-Hoang | Bao-Tran Pham-Hong | Yiping Jin | Phu T. V. Le
Proceedings of the 32nd Pacific Asia Conference on Language, Information and Computation

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