Fri, Jul 27, 2018 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Matt Gardner, Allen Institute for Artificial Intelligence AI2
Talk Title: A Tale of Two Question Answering Systems
Series: Natural Language Seminar
Abstract: The path to natural language understanding goes through increasingly challenging question answering tasks. I will present research that significantly improves performance on two such tasks: answering complex questions over tables, and open-domain factoid question answering. For answering complex questions, I will present a type-constrained encoder decoder neural semantic parser that learns to map natural language questions to programs. For open-domain factoid QA, I will show that training paragraph level QA systems to give calibrated confidence scores across paragraphs is crucial when the correct answer containing paragraph is unknown. I will conclude with some thoughts about how to combine these two disparate QA paradigms, towards the goal of answering complex questions over open-domain text.
Biography: Matt Gardner is a research scientist at the Allen Institute for Artificial Intelligence AI2, where he has been exploring various kinds of question answering systems. He is the lead designer and maintainer of the AllenNLP toolkit, a platform for doing NLP research on top of pytorch. Matt is also the cohost of the NLP Highlights podcast, where, with Waleed Ammar, he gets to interview the authors of interesting NLP papers about their work. Prior to joining AI2, Matt earned a PhD from Carnegie Mellon University, working with Tom Mitchell on the Never Ending Language Learning project.
Host: Nanyun Peng
More Info: http://nlg.isi.edu/nl-seminar/
Audiences: Everyone Is Invited
Contact: Peter Zamar