About this Event
2 W Loop Rd, New York, NY 10044
#CornellTechLearning Machines Seminar Series
What: LMSS: Wei Xu (Georgia Tech)
When: Friday, Sep 23, 12:15 p.m.
Where: Room 091, Bloomberg Center, Cornell Tech (map)
"Importance of Data and Controllability in Neural Language Generation"
Natural language generation has become a popular playground for deep learning techniques. In this talk, I will demonstrate that creating high-quality training data and introducing controllability over different editing operations (such as paraphrasing, sentence splitting, etc.) can lead to significant performance improvements that overshadow gains from model variations. In particular, I will focus on the text simplification task that improves text accessibility, including: (1) a monolingual word alignment model that can identify semantically related text spans between two sentences for analyzing human editing operations; (2) a controllable text generation approach that incorporates syntax through pairwise ranking and data argumentation; (3) a neural conditional random field (CRF) based semantic model to create parallel training data. I will also briefly discuss our other work on large-scale paraphrase acquisition from Twitter.
BIO
Wei Xu is an assistant professor in the School of Interactive Computing at the Georgia Institute of Technology. Xu received her Ph.D. in Computer Science from New York University, B.S. and M.S. from Tsinghua University. Her research interests are in natural language processing, machine learning, and social media. Her recent work focuses on text generation, semantics, information extraction, and reading assistive technology. She is a recipient of the NSF CAREER Award, CrowdFlower AI for Everyone Award, Criteo Faculty Research Award, and COLING Best Paper Award. She has also received funds from DARPA and IARPA, and is part of the new NSF AI CARING Institute.
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