Ph.D. Candidate, RL Lab, McGill University
I am a third year Ph.D. student in Computer Science in the Reasoning and Learning lab at McGill University and also a Ph.D. student at MILA, supervised by Dr. Jackie Cheung. I am broadly interested in the research area of artificial intelligence and natural language processing, particularly on applying deep learning and reinforcement learning techniques in natural language understanding and natural language generation.
My current research focuses on automatic text summarization and text simplification. I am also working on applying reinforcement learning in common sense reasoning and using graphical models for hierarchical text classification. In the past, I worked on using deep learning and reinforcement learning methods for extractive summarization.
I co-organized last year's CompLing meetings, a series of weekly seminars in which we host researchers from the industry and academia to discuss their research related to natural language processing and computational linguistics. To join the CompLing mailing list, please send an email to email@example.com.
I received my master's degree in mathematics from University of Ottawa in 2016, under the co-supervision of Dr. Vladimir Pestov and Dr. Nathalie Japkowicz. My master's thesis can be found here. Before that, I obtained my bachelor's degree with a major in mathematics and minor in computer science from University of Ottawa in 2014.
Yue Dong, Matt Grenander, Jackie Cheung, Annie Louis. "Countering the Effects of Lead Bias in News Summarization via Multi-Stage Training and Auxiliary Losses." EMNLP-IJCNLP (2019)
Yue Dong, Zichao Li, Mehdi Rezagholizadeh, Jackie Cheung. "EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing." ACL (2019)
Pengfei Liu, Yue Dong, Jie Fu, Xipeng Qiu, Jackie Cheung. "Learning Multi-task Communication with Message Passing for Sequence Learning." AAAI (2019)
Yue Dong, Yikang Shen, Eric Crawford, Herke van Hoof, Jackie Chi Kit Cheung. "BanditSum: Extractive Summarization as a Contextual Bandit." EMNLP (2018)
Koustuv Sinha, Yue Dong, Jackie Chi Kit Cheung and Derek Ruths. "A Hierarchical Neural Attention-based Text Classifier." EMNLP (2018)
Yue Dong. "A Survey on Neural Network-Based Summarization Methods." arXiv preprint arXiv:2199934 (2018)
Yue Dong, and Nathalie Japkowicz. "Threaded ensembles of autoencoders for stream learning." Computational Intelligence. Wiley. Volume34, Issue1, Pages 261-281, February 2018
Yue Dong, and Nathalie Japkowicz. "Threaded ensembles of supervised and unsupervised neural networks for stream learning." Canadian Conference on Artificial Intelligence. Springer, Cham, 2016. (won the best paper award)