2 citations · 2 across the 2 of their papers we have counts for
5 papers
Improve Event Extraction via Self-Training with Gradient Guidance
Zhiyang Xu, Jay-Yoon Lee, Lifu Huang
Data scarcity has been the main factor that hinders the progress of event extraction. To overcome this issue, we propose a Self-Training with Feedback (STF) framework that leverage…
Case-based Reasoning for Natural Language Queries over Knowledge Bases
Rajarshi Das, Manzil Zaheer, Dung Thai +6
It is often challenging to solve a complex problem from scratch, but much easier if we can access other similar problems with their solutions -- a paradigm known as case-based reas…
StructSum: Summarization via Structured Representations
Vidhisha Balachandran, Artidoro Pagnoni, Jay Yoon Lee +3
Abstractive text summarization aims at compressing the information of a long source document into a rephrased, condensed summary. Despite advances in modeling techniques, abstracti…
Towards Semi-Supervised Learning for Deep Semantic Role Labeling
Sanket Vaibhav Mehta, Jay Yoon Lee, Jaime Carbonell
Neural models have shown several state-of-the-art performances on Semantic Role Labeling (SRL). However, the neural models require an immense amount of semantic-role corpora and ar…
Gradient-based Inference for Networks with Output Constraints
Jay Yoon Lee, Sanket Vaibhav Mehta, Michael Wick +2
Practitioners apply neural networks to increasingly complex problems in natural language processing, such as syntactic parsing and semantic role labeling that have rich output stru…