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

Dietrich Klakow

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

8 / 8 papers shown

Title
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 34 16 0 25 Apr 2022
Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints Zichao Wang Andrew S. Lan Richard G. Baraniuk 64 45 0 09 Sep 2021
Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View Tianyu Liu Xin Zheng Baobao Chang Zhifang Sui 127 35 0 17 Feb 2021
Plan ahead: Self-Supervised Text Planning for Paragraph Completion Task Dongyeop Kang Eduard H. Hovy LRM 42 24 0 11 Oct 2020
Neural Data-to-Text Generation via Jointly Learning the Segmentation and Correspondence Xiaoyu Shen Ernie Chang Hui Su Jie Zhou Dietrich Klakow 37 49 0 03 May 2020
Unsupervised Pidgin Text Generation By Pivoting English Data and Self-Training Ernie Chang David Ifeoluwa Adelani Xiaoyu Shen Vera Demberg 6 21 0 18 Mar 2020
SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents Ramesh Nallapati Feifei Zhai Bowen Zhou 207 1,255 0 14 Nov 2016
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 218 7,925 0 17 Aug 2015