1 code implementation • EMNLP 2021 • Zhiyang Xu, Andrew Drozdov, Jay Yoon Lee, Tim O'Gorman, Subendhu Rongali, Dylan Finkbeiner, Shilpa Suresh, Mohit Iyyer, Andrew McCallum
For over thirty years, researchers have developed and analyzed methods for latent tree induction as an approach for unsupervised syntactic parsing.
1 code implementation • EACL 2021 • Vidhisha Balachandran, Artidoro Pagnoni, Jay Yoon Lee, Dheeraj Rajagopal, Jaime Carbonell, Yulia Tsvetkov
To this end, we propose incorporating latent and explicit dependencies across sentences in the source document into end-to-end single-document summarization models.
no code implementations • EMNLP 2018 • Sanket Vaibhav Mehta, Jay Yoon Lee, Jaime Carbonell
The paper proposes a semi-supervised semantic role labeling method that outperforms the state-of-the-art in limited SRL training corpora.
no code implementations • 26 Jul 2017 • Jay Yoon Lee, Sanket Vaibhav Mehta, Michael Wick, Jean-Baptiste Tristan, Jaime Carbonell
Practitioners apply neural networks to increasingly complex problems in natural language processing, such as syntactic parsing and semantic role labeling that have rich output structures.