We are glad to announce that Canadian AI 2020 has the following confirmed keynote speakers:
- Giuseppe Carenini (University of British Columbia),
- Pascal Poupart (University of Waterloo), and
- Csaba Szepesvari (University of Alberta),
as well as a tutorial by Pierre-Luc Bacon from MILA.
"Taming Discourse Parsing and Text Planning: an integrated AI approach towards a data-driven theory of Discourse"
Discourse parsing is a fundamental NLP task aiming to uncover the structure of coherent multi-sentential documents. Not only has discourse parsing been shown to enhance many key downstream tasks, like text classification, summarization and sentiment prediction, but it also appears to complement powerful contextual embeddings, like BERT, in tasks where discourse information is critical, such as argumentation analysis.
Historically, the development of effective discourse parsers has been hampered by the lack of annotated data, which often leads to overfitting and prevents the adoption of deep-learning solutions. In this talk, we will describe a novel approach that uses distant supervision to automatically generate abundant data to train discourse parsers. This approach synergistically combines several key AI techniques, including multiple instance learning, optimal tree parsing strategies and heuristic search algorithms inspired by reinforcement learning.
Remarkably, experiments indicate that this automatically generated treebank is superior to human-annotated corpora for training a discourse parser on the challenging and useful task of inter-domain discourse parsing, where the parser is trained on one domain (e.g., news) and tested/applied on another one (e.g., instruction manuals).
We conclude with a discussion of the potential of our approach to not only further boost performance on downstream tasks like sentiment analysis and summarization, but also in providing a new framework for text planning and more generally in moving towards a data-driven linguistic theory of discourse.
Giuseppe Carenini is a Professor in Computer Science at UBC (Vancouver, Canada). Giuseppe has broad interdisciplinary interests. His work on natural language processing and information visualization to support decision making has been published in over 120 peer-reviewed papers (including best paper at UMAP-14 and ACM-TiiS-14). Dr. Carenini was the area chair for ACL'09 in "Sentiment Analysis, Opinion Mining, and Text Classification", for NAACL'12, EMNLP'19 and ACL’20 in "Summarization and Generation", and for ACL'19 in "Discourse". He was also the Program Co-Chair for IUI 2015, and the Program Co-Chair for SigDial 2016. In 2011, he published a co-authored book on “Methods for Mining and Summarizing Text Conversations”. In his work, Dr. Carenini has also extensively collaborated with industrial partners, including Microsoft and IBM. Giuseppe was awarded a Google Research Award, an IBM CASCON Best Exhibit Award, and a Yahoo Faculty Research Award in 2007, 2010 and 2016 respectively.