RSVP Here

Title: Question Answering, Event Knowledge, and other NLP Stuff: Forays into Reuse, Decomposition, and Control in Neural NLP Models

Abstract: In this three-part talk, I will present some of our recent efforts that aim to control and adapt neural models to work more effectively in target applications. The first part will focus on how to repurpose a pre-trained neural entailment model for multi-hop QA, and decomposing large QA models to run effectively on mobile devices. In the second part, I will present methods for learning structured latent spaces for better control in modeling and generating event sequences. In the third part, I will talk briefly about modeling target-side syntax for machine translation. 

Bio: 

Niranjan is an Assistant Professor in the Computer Science department at Stony Brook University, where he heads the Language Understanding and Reasoning lab (LUNR). Prior to joining Stony Brook, he was a post-doctoral researcher at the University of Washington, and was one of the early members of the Allen Institute for Artificial Intelligence. Niranjan completed his Ph.D. in Computer Science from the University of Massachusetts Amherst. 

He likes food and wine just enough that he sometimes wants to mention it as part of his bio and is a categorically amateurish paint splatterer that he does not (yet) want to mention it as part of his bio.