MQLL Meeting, 10/17

At next week’s meeting, Wilfred will be presenting the following paper: “Learning Semantic Correspondence with Less Supervision” by Liang et al. (2009). Please find the abstract below:

A central problem in grounded language acquisition is learning the correspondences between a rich world state and a stream of text which references that world state. To deal with the high de- gree of ambiguity present in this setting, we present a generative model that simultaneously segments the text into utterances and maps each utterance to a meaning representation grounded in the world state. We show that our model generalizes across three domains of increasing difficulty—Robocup sportscasting, weather forecasts (a new domain), and NFL recaps.

Meeting will be Wednesday Oct 17 from 5:30pm to 7:30pm at room 117.

Comments are closed.

Blog authors are solely responsible for the content of the blogs listed in the directory. Neither the content of these blogs, nor the links to other web sites, are screened, approved, reviewed or endorsed by McGill University. The text and other material on these blogs are the opinion of the specific author and are not statements of advice, opinion, or information of McGill.