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Select and Attend: Towards Controllable Content Selection in Text
  Generation

Select and Attend: Towards Controllable Content Selection in Text Generation

10 September 2019
Xiaoyu Shen
Jun Suzuki
Kentaro Inui
Hui Su
Dietrich Klakow
Satoshi Sekine
ArXivPDFHTML

Papers citing "Select and Attend: Towards Controllable Content Selection in Text Generation"

6 / 6 papers shown
Title
ED2LM: Encoder-Decoder to Language Model for Faster Document Re-ranking
  Inference
ED2LM: Encoder-Decoder to Language Model for Faster Document Re-ranking Inference
Kai Hui
Honglei Zhuang
Tao Chen
Zhen Qin
Jing Lu
...
Ji Ma
Jai Gupta
Cicero Nogueira dos Santos
Yi Tay
Donald Metzler
28
16
0
25 Apr 2022
Math Word Problem Generation with Mathematical Consistency and Problem
  Context Constraints
Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints
Zichao Wang
Andrew S. Lan
Richard G. Baraniuk
60
45
0
09 Sep 2021
Towards Faithfulness in Open Domain Table-to-text Generation from an
  Entity-centric View
Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View
Tianyu Liu
Xin Zheng
Baobao Chang
Zhifang Sui
119
35
0
17 Feb 2021
Plan ahead: Self-Supervised Text Planning for Paragraph Completion Task
Plan ahead: Self-Supervised Text Planning for Paragraph Completion Task
Dongyeop Kang
Eduard H. Hovy
LRM
34
24
0
11 Oct 2020
SummaRuNNer: A Recurrent Neural Network based Sequence Model for
  Extractive Summarization of Documents
SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents
Ramesh Nallapati
Feifei Zhai
Bowen Zhou
207
1,254
0
14 Nov 2016
Effective Approaches to Attention-based Neural Machine Translation
Effective Approaches to Attention-based Neural Machine Translation
Thang Luong
Hieu H. Pham
Christopher D. Manning
216
7,923
0
17 Aug 2015
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