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Challenges in Data-to-Document Generation
Sam Wiseman
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Stuart Shieber
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Alexander Rush
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Paper Details:
Month: September
Year: 2017
Location: Copenhagen, Denmark
Venue:
EMNLP |
Citations
URL
Point Precisely: Towards Ensuring the Precision of Data in Generated Texts Using Delayed Copy Mechanism
Liunian Li
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Xiaojun Wan
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Guided Neural Language Generation for Abstractive Summarization using Abstract Meaning Representation
Hardy Hardy
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Andreas Vlachos
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Logician and Orator: Learning from the Duality between Language and Knowledge in Open Domain
Mingming Sun
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Xu Li
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Ping Li
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Learning Neural Templates for Text Generation
Sam Wiseman
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Stuart Shieber
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Alexander Rush
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Learning Latent Semantic Annotations for Grounding Natural Language to Structured Data
Guanghui Qin
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Jin-Ge Yao
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Xuening Wang
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Jinpeng Wang
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Chin-Yew Lin
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Operation-guided Neural Networks for High Fidelity Data-To-Text Generation
Feng Nie
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Jinpeng Wang
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Jin-Ge Yao
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Rong Pan
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Chin-Yew Lin
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Incorporating Background Knowledge into Video Description Generation
Spencer Whitehead
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Heng Ji
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Mohit Bansal
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Shih-Fu Chang
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Clare Voss
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Data2Text Studio: Automated Text Generation from Structured Data
Longxu Dou
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Guanghui Qin
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Jinpeng Wang
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Jin-Ge Yao
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Chin-Yew Lin
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Discourse-Aware Neural Rewards for Coherent Text Generation
Antoine Bosselut
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Asli Celikyilmaz
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Xiaodong He
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Jianfeng Gao
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Po-Sen Huang
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Yejin Choi
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Bootstrapping Generators from Noisy Data
Laura Perez-Beltrachini
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Mirella Lapata
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A Mixed Hierarchical Attention Based Encoder-Decoder Approach for Standard Table Summarization
Parag Jain
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Anirban Laha
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Karthik Sankaranarayanan
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Preksha Nema
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Mitesh M. Khapra
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Shreyas Shetty
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Learning to Write with Cooperative Discriminators
Ari Holtzman
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Jan Buys
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Maxwell Forbes
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Antoine Bosselut
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David Golub
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Yejin Choi
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Automatic Article Commenting: the Task and Dataset
Lianhui Qin
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Lemao Liu
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Wei Bi
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Yan Wang
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Xiaojiang Liu
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Zhiting Hu
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Hai Zhao
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Shuming Shi
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Deep Graph Convolutional Encoders for Structured Data to Text Generation
Diego Marcheggiani
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Laura Perez-Beltrachini
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Describing a Knowledge Base
Qingyun Wang
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Xiaoman Pan
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Lifu Huang
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Boliang Zhang
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Zhiying Jiang
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Heng Ji
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Kevin Knight
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Automated learning of templates for data-to-text generation: comparing rule-based, statistical and neural methods
Chris van der Lee
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Emiel Krahmer
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Sander Wubben
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LSTM Hypertagging
Reid Fu
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Michael White
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Sequence-to-Sequence Models for Data-to-Text Natural Language Generation: Word- vs. Character-based Processing and Output Diversity
Glorianna Jagfeld
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Sabrina Jenne
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Ngoc Thang Vu
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E2E NLG Challenge Submission: Towards Controllable Generation of Diverse Natural Language
Henry Elder
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Sebastian Gehrmann
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Alexander O’Connor
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Qun Liu
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https://github.com/
https://github.com/harvardnlp/
https://ehudreiter.com/2017/05/
Field Of Study
Task
Semantic Parsing
Information Extraction
Relation Extraction
Language Generation
Machine Translation
Approach
Semi-supervised Learning
Language
English
Dataset
Biographies
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