Department of Mathematics and Statistics

Department of Mathematics and Statistics
Department of Mathematics and Statistics

Joint Seminars in Statistics & Biostatistics


Thursday, April 1st, 2021

Time: 4:00pm Place:

Speaker: Bang Liu (University of Montreal)

Title: Data, Knowledge, and Logic: Modeling and Reasoning for Natural Language Understanding.

Abstract: Existing deep learning-based techniques for different NLU tasks are mostly data-intensive and domain-sensitive. However, creating large-amount and high-quality training datasets for NLU tasks, e.g., question answering, are both expensive and time-consuming. In this talk, we will introduce our research on data generation, knowledge expansion, and reasoning over graphs. Specifically, for data augmentation, we generate large-scale and high-quality question-answer pairs from unlabeled text to augment the training data for question answering. For knowledge expansion, we create and expand an ontology with newly discovered concepts or entities to capture the emerging knowledge in the world and keep the ontology dynamically updated. For reasoning over graphs, we propose a reinforcement learning-based relational reasoning framework, R5, that reasons over relational data and learns the underlying compositional logical rules. Our long-term vision is to design low-resource, knowledge-empowered, and transferable NLU systems and apply them to different domains.