108 citations · 505 across the 38 of their papers we have counts for
12 papers · 1 filter
Automatic Detection of Vague Words and Sentences in Privacy Policies
Logan Lebanoff, Fei Liu
Website privacy policies represent the single most important source of information for users to gauge how their personal data are collected, used and shared by companies. However,…
Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document Summarization
Logan Lebanoff, Kaiqiang Song, Fei Liu
Generating a text abstract from a set of documents remains a challenging task. The neural encoder-decoder framework has recently been exploited to summarize single documents, but i…
A Novel ILP Framework for Summarizing Content with High Lexical Variety
Wencan Luo, Fei Liu, Zitao Liu +1
Summarizing content contributed by individuals can be challenging, because people make different lexical choices even when describing the same events. However, there remains a sign…
Structure-Infused Copy Mechanisms for Abstractive Summarization
Kaiqiang Song, Lin Zhao, Fei Liu
Seq2seq learning has produced promising results on summarization. However, in many cases, system summaries still struggle to keep the meaning of the original intact. They may miss…
Reinforced Extractive Summarization with Question-Focused Rewards
Kristjan Arumae, Fei Liu
We investigate a new training paradigm for extractive summarization. Traditionally, human abstracts are used to derive goldstandard labels for extraction units. However, the labels…
Abstract Meaning Representation for Multi-Document Summarization
Kexin Liao, Logan Lebanoff, Fei Liu
Generating an abstract from a collection of documents is a desirable capability for many real-world applications. However, abstractive approaches to multi-document summarization ha…