37 citations · 50 across the 7 of their papers we have counts for
5 papers · 1 filter
Knowledge-grounded Natural Language Recommendation Explanation
Anthony Colas, Jun Araki, Zhengyu Zhou +2
Explanations accompanied by a recommendation can assist users in understanding the decision made by recommendation systems, which in turn increases a user's confidence and trust in…
Modeling Endorsement for Multi-Document Abstractive Summarization
Logan Lebanoff, Bingqing Wang, Zhe Feng +1
A crucial difference between single- and multi-document summarization is how salient content manifests itself in the document(s). While such content may appear at the beginning of…
GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
Xinyan Zhao, Haibo Ding, Zhe Feng
Instead of using expensive manual annotations, researchers have proposed to train named entity recognition (NER) systems using heuristic labeling rules. However, devising labeling…
A New Approach to Overgenerating and Scoring Abstractive Summaries
Kaiqiang Song, Bingqing Wang, Zhe Feng +1
We propose a new approach to generate multiple variants of the target summary with diverse content and varying lengths, then score and select admissible ones according to users' ne…
Controlling the Amount of Verbatim Copying in Abstractive Summarization
Kaiqiang Song, Bingqing Wang, Zhe Feng +2
An abstract must not change the meaning of the original text. A single most effective way to achieve that is to increase the amount of copying while still allowing for text abstrac…