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PRODID:-//Cornell U. Department of Computer Science//Brown Bag Seminar//EN
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SUMMARY:Brown bag: Yoav Artzi
DESCRIPTION:Title: Context-dependent Natural Language
	 Understanding\nSpeaker: Yoav Artzi\nAbstract: Understanding natural
	 language requires considering both sentence meaning and signals from the
	 context of the interaction. In this talk\, I will describe two projects
	 about learning to map context-dependent sentences to code or system
	 actions. In the first\, we generate SQL code from natural language
	 queries to a database. The user provides the queries within an
	 interaction where it gradually refines their intention based on the
	 system response. The queries are heavily dependent on the history of the
	 interaction\, and require generating long and complex SQL queries. We
	 show that intelligently copying segments from previous queries instead
	 of generating from scratch effectively captures the referential
	 structure of the interaction. The second project addresses a scenario
	 where the user instruct an agent to act in an environment using natural
	 language instructions. We show that using representation learning
	 without any explicit modeling of meaning or context to directly generate
	 actions significantly improves execution accuracy by up to 68% by
	 removing implicitly introduced assumptions.
LOCATION:Gates 122
UID:2018-09-25
STATUS:TENTATIVE
DTSTART:20180925T160000Z
DTEND:20180925T170000Z
LAST-MODIFIED:20180923T161910Z
ORGANIZER;CN=Jonathan Shi:http://www.cs.cornell.edu/~jshi/brownbag/
DTSTAMP:20260408T121928Z
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