activity
20162021
most citedScoring Sentence Singletons and Pairs for Abstractive Summarization

8 citations · 18 across the 4 of their papers we have counts for

collaborators

12 papers

cs.CL2021

MadDog: A Web-based System for Acronym Identification and Disambiguation

Amir Pouran Ben Veyseh, Franck Dernoncourt, Walter Chang +1

Acronyms and abbreviations are the short-form of longer phrases and they are ubiquitously employed in various types of writing. Despite their usefulness to save space in writing an…

cs.CL2020

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…

cs.CL2020

A Cascade Approach to Neural Abstractive Summarization with Content Selection and Fusion

Logan Lebanoff, Franck Dernoncourt, Doo Soon Kim +2

We present an empirical study in favor of a cascade architecture to neural text summarization. Summarization practices vary widely but few other than news summarization can provide…

cs.CL20203 cited

Interaction Matching for Long-Tail Multi-Label Classification

Sean MacAvaney, Franck Dernoncourt, Walter Chang +2

We present an elegant and effective approach for addressing limitations in existing multi-label classification models by incorporating interaction matching, a concept shown to be u…

cs.CL2020

Variational Hierarchical Dialog Autoencoder for Dialog State Tracking Data Augmentation

Kang Min Yoo, Hanbit Lee, Franck Dernoncourt +3

Recent works have shown that generative data augmentation, where synthetic samples generated from deep generative models complement the training dataset, benefit NLP tasks. In this…

cs.CL2019

Rethinking Self-Attention: Towards Interpretability in Neural Parsing

Khalil Mrini, Franck Dernoncourt, Quan Tran +3

Attention mechanisms have improved the performance of NLP tasks while allowing models to remain explainable. Self-attention is currently widely used, however interpretability is di…