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Graph-based Neural Multi-Document Summarization
Michihiro Yasunaga
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Rui Zhang
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Kshitijh Meelu
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Ayush Pareek
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Krishnan Srinivasan
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Dragomir Radev
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Paper Details:
Month: August
Year: 2017
Location: Vancouver, Canada
Venue:
CoNLL |
SIG: SIGNLL
Citations
URL
On the Abstractiveness of Neural Document Summarization
Fangfang Zhang
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Jin-ge Yao
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Rui Yan
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BanditSum: Extractive Summarization as a Contextual Bandit
Yue Dong
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Yikang Shen
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Eric Crawford
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Herke van Hoof
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Jackie Chi Kit Cheung
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Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document Summarization
Logan Lebanoff
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Kaiqiang Song
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Fei Liu
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Ranking Sentences for Extractive Summarization with Reinforcement Learning
Shashi Narayan
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Shay B. Cohen
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Mirella Lapata
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Guiding Generation for Abstractive Text Summarization Based on Key Information Guide Network
Chenliang Li
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Weiran Xu
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Si Li
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Sheng Gao
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A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss
Wan-Ting Hsu
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Chieh-Kai Lin
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Ming-Ying Lee
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Kerui Min
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Jing Tang
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Min Sun
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Dating Documents using Graph Convolution Networks
Shikhar Vashishth
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Shib Sankar Dasgupta
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Swayambhu Nath Ray
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Partha Talukdar
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Towards Opinion Summarization of Customer Reviews
Samuel Pecar
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No URLs Found
Field Of Study
Linguistic Trends
Discourse
Embeddings
Task
Summarization
Machine Translation
Approach
Deep Learning
Representation Learning
Language
Multilingual
English
Dataset
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