35 citations · 51 across the 6 of their papers we have counts for
3 papers · 1 filter
Leveraging Information Bottleneck for Scientific Document Summarization
Jiaxin Ju, Ming Liu, Huan Yee Koh +3
This paper presents an unsupervised extractive approach to summarize scientific long documents based on the Information Bottleneck principle. Inspired by previous work which uses t…
SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression
Jinming Zhao, Ming Liu, Longxiang Gao +5
Obtaining training data for multi-document summarization (MDS) is time consuming and resource-intensive, so recent neural models can only be trained for limited domains. In this pa…
Improving Topic Models with Latent Feature Word Representations
Dat Quoc Nguyen, Richard Billingsley, Lan Du +1
Probabilistic topic models are widely used to discover latent topics in document collections, while latent feature vector representations of words have been used to obtain high per…