74 citations · 86 across the 5 of their papers we have counts for
5 papers
Learning to Fuse Sentences with Transformers for Summarization
Logan Lebanoff, Franck Dernoncourt, Doo Soon Kim +3
The ability to fuse sentences is highly attractive for summarization systems because it is an essential step to produce succinct abstracts. However, to date, summarizers can fail o…
Bayesian Optimization for Selecting Efficient Machine Learning Models
Lidan Wang, Franck Dernoncourt, Trung Bui
The performance of many machine learning models depends on their hyper-parameter settings. Bayesian Optimization has become a successful tool for hyper-parameter optimization of ma…
Understanding Points of Correspondence between Sentences for Abstractive Summarization
Logan Lebanoff, John Muchovej, Franck Dernoncourt +4
Fusing sentences containing disparate content is a remarkable human ability that helps create informative and succinct summaries. Such a simple task for humans has remained challen…
Open-Domain Question Answering with Pre-Constructed Question Spaces
Jinfeng Xiao, Lidan Wang, Franck Dernoncourt +3
Open-domain question answering aims at solving the task of locating the answers to user-generated questions in massive collections of documents. There are two families of solutions…
Applying Deep Learning to Answer Selection: A Study and An Open Task
Minwei Feng, Bing Xiang, Michael R. Glass +2
We apply a general deep learning framework to address the non-factoid question answering task. Our approach does not rely on any linguistic tools and can be applied to different la…