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Data-to-text-Paper-List

A summary of Data-to-text Generation Papers.

Content

Data
Public Datasets Corpora Generation and Manipulation
Data Augmentation
Analysis
Models
Data Representation Content Generation
Surface Realization Other Directions
Training Methods
Evaluation
Applications
Thesis

Data

Public Datasets

  1. Challenges in Data-to-Document Generation EMNLP, 2017 paper

    Sam Wiseman; Stuart M. Shieber; Alexander M. Rush

  2. Creating Training Corpora for NLG Micro-Planners ACL, 2017 paper

    Claire Gardent; Anastasia Shimorina; Shashi Narayan; Laura Perez-Beltrachini

  3. Creating a Corpus for Russian Data-to-Text Generation Using Neural Machine Translation and Post-Editing BSNLP@ACL, 2019 paper

    Anastasia Shimorina; Elena Khasanova; Claire Gardent

  4. Ensuring Readability and Data-fidelity using Head-modifier Templates in Deep Type Description Generation ACL, 2019 paper

    Jiangjie Chen; Ao Wang; Haiyun Jiang; Suo Feng; Chenguang Li; Yanghua Xiao

  5. ViGGO: A Video Game Corpus for Data-To-Text Generation in Open-Domain Conversation. INLG, 2019 paper

    Juraj Juraska; Kevin K. Bowden; Marilyn A. Walker

  6. The CACAPO Dataset : A Multilingual, Multi-Domain Dataset for Neural Pipeline and End-to-End Data-to-Text Generation INLG, 2020 paper

    Chris van der Lee; Chris Emmery; Sander Wubben; Emiel Krahmer

  7. ToTTo: A Controlled Table-To-Text Generation Dataset EMNLP, 2020 paper

    Ankur P. Parikh; Xuezhi Wang; Sebastian Gehrmann; Manaal Faruqui; Bhuwan Dhingra; Diyi Yang; Dipanjan Das

  8. Plum2Text: a french plumitifs -descriptions data-to-text dataset for natural language generation ICAIL, 2021 paper

    Nicolas Garneau; Eve Gaumond; Luc Lamontagne; Pierre-Luc Déziel

  9. Towards Table-to-Text Generation with Numerical Reasoning ACL/IJCNLP, 2021 paper

    Lya Hulliyyatus Suadaa; Hidetaka Kamigaito; Kotaro Funakoshi; Manabu Okumura; Hiroya Takamura

Corpora Generation

  1. Schema-Guided Natural Language Generation. INLG, 2020 paper

    Yuheng Du; Shereen Oraby; Vittorio Perera; Minmin Shen; Anjali Narayan-Chen; Tagyoung Chung; Anu Venkatesh; Dilek Hakkani-Tur

  2. Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training NAACL-HLT, 2021 paper

    Oshin Agarwal; Heming Ge; Siamak Shakeri; Rami Al-Rfou

Data Augmentation

  1. Neural Data-to-Text Generation with LM-based Text Augmentation EACL, 2021 paper

    Ernie Chang; Xiaoyu Shen; Dawei Zhu; Vera Demberg; Hui Su

  2. Automatic Construction of Evaluation Suites for Natural Language Generation Datasets arXiv, 2021 paper

    Simon Mille; Kaustubh Dhole; Saad Mahamood; Laura Perez-Beltrachini; Varun Gangal; Mihir Kale; Emiel van Miltenburg; Sebastian Gehrmann

Analysis

  1. Automated learning of templates for data-to-text generation: comparing rule-based, statistical and neural methods INLG, 2018 paper

    Chris van der Lee; Emiel Krahmer; Sander Wubben

  2. Handling Rare Items in Data-to-Text Generation INLG, 2018 paper

    Anastasia Shimorina; Claire Gardent

  3. Sequence-to-Sequence Models for Data-to-Text Natural Language Generation:Word- vs. Character-based Processing and Output Diversity INLG, 2018 paper

    Glorianna Jagfeld; Sabrina Jenne; Ngoc Thang Vu

  4. A Closer Look at Recent Results of Verb Selection for Data-to-Text NLG. INLG, 2019 paper

    Guanyi Chen; Jin-Ge Yao

  5. Neural data-to-text generation: A comparison between pipeline and end-to-end architectures EMNLP/IJCNLP, 2019 paper

    Thiago Castro Ferreira; Chris van der Lee; Emiel van Miltenburg; Emiel Krahmer

  6. Remodeling Numerical Representation for Text Generation on Small Corpus: A Syntactical Analysis Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence, 2019 paper

    Aristotle Tan; Hui-Ngo Goh; Lai-Kuan Wong

  7. On Hallucination and Predictive Uncertainty in Conditional Language Generation EACL, 2021 paper

    Yijun Xiao; William Yang Wang

Models

Data Representation

  1. Table-to-text Generation by Structure-aware Seq2seq Learning arXiv, 2017 paper

    Tianyu Liu; Kexiang Wang; Lei Sha; Baobao Chang; Zhifang Sui

  2. A Hierarchical Model for Data-to-Text Generation arXiv, 2019 paper

    Clément Rebuffel; Laure Soulier; Geoffrey Scoutheeten; Patrick Gallinari

  3. Data-to-Text Generation with Attention Recurrent Unit IJCNN, 2019 paper

    Hechong Wang; Wei Zhang; Yuesheng Zhu; Zhiqiang Bai

  4. Data-to-text Generation with Entity Modeling ACL, 2019 paper

    Ratish Puduppully; Li Dong; Mirella Lapata

  5. Hierarchical Encoder with Auxiliary Supervision for Neural Table-to-Text Generation: Learning Better Representation for Tables AAAI, 2019 paper

    Tianyu Liu; Fuli Luo; Qiaolin Xia; Shuming Ma; Baobao Chang; Zhifang Sui

  6. Table-to-Text Natural Language Generation with Unseen Schemas. arXiv, 2019 paper

    Tianyu Liu; Wei Wei; William Yang Wang

  7. A Hierarchical Model for Data-to-Text Generation ECIR, 2020 paper

    Clément Rebuffel; Laure Soulier; Geoffrey Scoutheeten; Patrick Gallinari

  8. Capturing Entity Hierarchy in Data-to-Text Generative Models. CIRCLE, 2020 paper

    Clément Rebuffel; Laure Soulier; Geoffrey Scoutheeten; Patrick Gallinari

  9. Data-to-text Generation with Pointer-Generator Networks AEECA, 2020 paper

    Mengzhu Liu; Zhaonan Mu; Jieping Sun; Cheng Wang

  10. Learning Better Representation for Tables by Self-Supervised Tasks. arXiv, 2020 paper

    Liang Li; Can Ma; Yinliang Yue; Linjun Shou; Dayong Hu

  11. Exploring Structural Encoding for Data-to-Text Generation. INLG, 2021 paper

    Joy Mahapatra; Utpal Garain

  12. TABBIE: Pretrained Representations of Tabular Data NAACL-HLT, 2021 paper

    Hiroshi Iida; Dung Thai; Varun Manjunatha; Mohit Iyyer

Content Generation

Semantic-accuracy

  1. Operation-guided Neural Networks for High Fidelity Data-To-Text Generation EMNLP, 2018 paper

    Feng Nie; Jinpeng Wang; Jin-Ge Yao; Rong Pan; Chin-Yew Lin

  2. Beyond Word for Word: Fact Guided Training for Neural Data-to-Document Generation NLPCC, 2019 paper

    Feng Nie; Hailin Chen; Jinpeng Wang; Rong Pan; Chin-Yew Lin

  3. Enhancing Neural Data-To-Text Generation Models with External Background Knowledge EMNLP/IJCNLP, 2019 paper

    Shuang Chen; Jinpeng Wang; Xiaocheng Feng; Feng Jiang; Bing Qin; Chin-Yew Lin

  4. Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation NAACL-HLT, 2019 paper

    Amit Moryossef; Yoav Goldberg; Ido Dagan

  5. Sticking to the Facts: Confident Decoding for Faithful Data-to-Text Generation. arXiv, 2019 paper

    Ran Tian; Shashi Narayan; Thibault Sellam; Ankur P. Parikh

  6. Table-to-Text Generation via Row-Aware Hierarchical Encoder CCL, 2019 paper

    Heng Gong; Xiaocheng Feng; Bing Qin; Ting Liu

  7. Data-to-Text Generation with Iterative Text Editing. INLG, 2020 paper

    Zdenek Kasner; Ondrej Dusek

  8. Neural Data-to-Text Generation via Jointly Learning the Segmentation and Correspondence ACL, 2020 paper

    Xiaoyu Shen; Ernie Chang; Hui Su; Cheng Niu; Dietrich Klakow

  9. A case-based approach to data-to-text generation. ICCBR, 2021 paper

    Ashish Upadhyay; Stewart Massie; Ritwik Kumar Singh; Garima Gupta; Muneendra Ojha

  10. Attention Is Indeed All You Need: Semantically Attention-Guided Decoding for Data-to-Text NLG. INLG, 2021 paper

    Juraj Juraska; Marilyn A. Walker

  11. Control Prefixes for Text Generation. arXiv, 2021 paper

    Jordan Clive; Kris Cao; Marek Rei

  12. Controlling hallucinations at word level in data-to-text generation Data Mining and Knowledge Discovery, 2021 paper

    Clément Rebuffel; Marco Roberti; Laure Soulier; Geoffrey Scoutheeten; Rossella Cancelliere; Patrick Gallinari

  13. Generative adversarial network for Table-to-Text generation Neurocomputing, 2021 paper

    Jianyu Zhao; Zhiqiang Zhan; Tong Li; Rang Li; Changjian Hu; Siyun Wang; Yang Zhang

Reasoning

  1. Towards Table-to-Text Generation with Numerical Reasoning ACL/IJCNLP, 2021 paper

    Lya Hulliyyatus Suadaa; Hidetaka Kamigaito; Kotaro Funakoshi; Manabu Okumura; Hiroya Takamura

Content Planning

  1. Order-Planning Neural Text Generation From Structured Data AAAI, 2017 paper

    Lei Sha; Lili Mou; Tianyu Liu; Pascal Poupart; Sujian Li; Baobao Chang; Zhifang Sui

  2. Data-to-Text Generation with Content Selection and Planning AAAI, 2019 paper

    Ratish Puduppully; Li Dong; Mirella Lapata

  3. End-to-End Content and Plan Selection for Data-to-Text Generation INLG, 2018 paper

    Sebastian Gehrmann; Falcon Z. Dai; Henry Elder; Alexander M. Rush

  4. Fine-Grained Control of Sentence Segmentation and Entity Positioning in Neural NLG Proceedings of the 1st Workshop on Discourse Structure in Neural NLG, 2019 paper

    Kritika Mehta; Raheel Qader; Cyril Labbé; François Portet

  5. Improving Quality and Efficiency in Plan-based Neural Data-to-text Generation INLG, 2019 paper

    Amit Moryossef; Yoav Goldberg; Ido Dagan

  6. Sentence generation for entity description with content-plan attention AAAI, 2020 paper

    Bayu Distiawan Trisedya; Jianzhong Qi; Rui Zhang

  7. AggGen: Ordering and Aggregating while Generating ACL/IJCNLP, 2021 paper

    Xinnuo Xu; Ondřej Dušek; Verena Rieser; Ioannis Konstas

  8. Data-to-text Generation with Macro Planning Transactions of the Association for Computational Linguistics, 2021 paper

    Ratish Puduppully; Mirella Lapata

  9. Grouped-Attention for Content-Selection and Content-Plan Generation EMNLP (Findings), 2021 paper

    Bayu Distiawan Trisedya; Xiaojie Wang; Jianzhong Qi; Rui Zhang; Qingjun Cui

  10. Plan-then-Generate: Controlled Data-to-Text Generation via Planning arXiv, 2021 paper

    Yixuan Su; David Vandyke; Sihui Wang; Yimai Fang; Nigel Collier

Surface Realization

Text Quality

  1. Probabilistic Verb Selection for Data-to-Text Generation Transactions of the Association for Computational Linguistics, 2018 paper

    Dell Zhang; Jiahao Yuan; Xiaoling Wang; Adam Foster

  2. Table-to-Text: Describing Table Region With Natural Language. AAAI, 2018 paper

    Junwei Bao; Duyu Tang; Nan Duan; Zhao Yan; Yuanhua Lv; Ming Zhou; Tiejun Zhao

  3. Ensuring Readability and Data-fidelity using Head-modifier Templates in Deep Type Description Generation ACL, 2019 paper

    Jiangjie Chen; Ao Wang; Haiyun Jiang; Suo Feng; Chenguang Li; Yanghua Xiao

  4. Long and Diverse Text Generation with Planning-based Hierarchical Variational Model EMNLP/IJCNLP, 2019 paper

    Zhihong Shao; Minlie Huang; Jiangtao Wen; Wenfei Xu; Xiaoyan Zhu

  5. Narrative context-based data-to-text generation for ambient intelligence Journal of Ambient Intelligence and Humanized Computing, 2019 paper

    Jungsun Jang; Hyungjong Noh; Yeonsoo Lee; Soo Min Pantel; Hae-Chang Rim

  6. Consistent Data-to-Text Generation with Topic Sequences JSAI, 2020 paper

    Soichiro Murakami

  7. Latent Template Induction with Gumbel-CRFs NeurIPS, 2020 paper

    Yao Fu; Chuanqi Tan; Bin Bi; Mosha Chen; Yansong Feng; Alexander M. Rush

  8. Learning with Contrastive Examples for Data-to-Text Generation COLING, 2020 paper

    Yui Uehara; Tatsuya Ishigaki; Kasumi Aoki; Hiroshi Noji; Keiichi Goshima; Ichiro Kobayashi; Hiroya Takamura; Yusuke Miyao

  9. Make Templates Smarter: A Template Based Data2Text System Powered by Text Stitch Model EMNLP (Findings), 2020 paper

    Bingfeng Luo; Bai Zuo; Kunfeng Lai; Jianping Shen

  10. Template-Based Multi-solution Approach for Data-to-Text Generation ADBIS, 2020 paper

    Abelardo Vieira Mota; Ticiana L. Coelho da Silva; José Antônio Fernandes de Macêdo

  11. Variational Template Machine for Data-to-Text Generation ICLR, 2020 paper

    Rong Ye; Wenxian Shi; Hao Zhou; Zhongyu Wei; Lei Li

  12. A case-based approach to data-to-text generation. ICCBR, 2021 paper

    Ashish Upadhyay; Stewart Massie; Ritwik Kumar Singh; Garima Gupta; Muneendra Ojha

  13. De-Confounded Variational Encoder-Decoder for Logical Table-to-Text Generation ACL/IJCNLP, 2021 paper

    Wenqing Chen; Jidong Tian; Yitian Li; Hao He; Yaohui Jin

  14. Generative adversarial network for Table-to-Text generation Neurocomputing, 2021 paper

    Jianyu Zhao; Zhiqiang Zhan; Tong Li; Rang Li; Changjian Hu; Siyun Wang; Yang Zhang

Writing Style

  1. Data-to-Text Generation with Style Imitation arXiv, 2019 paper

    Shuai Lin; Wentao Wang; Zichao Yang; Xiaodan Liang; Frank F. Xu; Eric P. Xing; Zhiting Hu

  2. Natural Language Generation for Non-Expert Users Electronic Proceedings in Theoretical Computer Science, 2019 paper

    Van Nguyen; Tran Cao Son; Enrico Pontelli

  3. Text Generation with Exemplar-based Adaptive Decoding NAACL-HLT, 2019 paper

    Hao Peng; Ankur P. Parikh; Manaal Faruqui; Bhuwan Dhingra; Dipanjan Das

  4. Data-to-Text Generation with Style Imitation EMNLP, 2020 paper

    Shuai Lin; Wentao Wang; Zichao Yang; Xiaodan Liang; Frank F. Xu; Eric P. Xing; Zhiting Hu

Other Directions

Limited Data

  1. A Novel Task-Oriented Text Corpus in Silent Speech Recognition and its Natural Language Generation Construction Method NLPIR, 2019 paper

    Dong Cao; Dongdong Zhang; Haibo Chen

  2. Key Fact as Pivot: A Two-Stage Model for Low Resource Table-to-Text Generation ACL, 2019 paper

    Shuming Ma; Pengcheng Yang; Tianyu Liu; Peng Li; Jie Zhou; Xu Sun

  3. KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation EMNLP, 2020 paper

    Wenhu Chen; Yu Su; Xifeng Yan; William Yang Wang

  4. TableGPT: Few-shot Table-to-Text Generation with Table Structure Reconstruction and Content Matching COLING, 2020 paper

    Heng Gong; Yawei Sun; Xiaocheng Feng; Bing Qin; Wei Bi; Xiaojiang Liu; Ting Liu

  5. Template-Based Multi-solution Approach for Data-to-Text Generation ADBIS, 2020 paper

    Abelardo Vieira Mota; Ticiana L. Coelho da Silva; José Antônio Fernandes de Macêdo

  6. Text-to-Text Pre-Training for Data-to-Text Tasks INLG, 2020 paper

    Mihir Kale

Interpretability and Controlability

  1. Select and Attend: Towards Controllable Content Selection in Text Generation EMNLP/IJCNLP 2019, http://dx.doi.org/10.18653/v1/d19-1054 [paper](Xiaoyu Shen; Jun Suzuki; Kentaro Inui; Hui Su; Dietrich Klakow; Satoshi Sekine)

    **

  2. Scalable Micro-planned Generation of Discourse from Structured Data Computational Linguistics 2019, http://dx.doi.org/10.1162/coli_a_00363 [paper](Anirban Laha; Parag Jain; Abhijit Mishra; Karthik Sankaranarayanan)

    **

  3. Data-to-text Generation by Splicing Together Nearest Neighbors EMNLP 2021, https://aclanthology.org/2021.emnlp-main.352/ [paper](Sam Wiseman; Arturs Backurs; Karl Stratos)

    **

  4. GenNI: Human-AI Collaboration for Data-Backed Text Generation. IEEE transactions on visualization and computer graphics, 2021 paper

    Hendrik Strobelt; Jambay Kinley; Robert Krueger; Johanna Beyer; Hanspeter Pfister; Alexander M. Rush

Others

  1. Towards Automatic Generation of Product Reviews from Aspect-Sentiment Scores INLG, 2017 paper

    Hongyu Zang; Xiaojun Wan

  2. Controlling contents in data-to-document generation with human-designed topic labels INLG, 2019 paper

    Kasumi Aoki; Akira Miyazawa; Tatsuya Ishigaki; Tatsuya Aoki; Hiroshi Noji; Keiichi Goshima; Ichiro Kobayashi; Hiroya Takamura; Yusuke Miyao

  3. Copy Mechanism and Tailored Training for Character-Based Data-to-Text Generation ECML/PKDD, 2020 paper

    Marco Roberti; Giovanni Bonetta; Rossella Cancelliere; Patrick Gallinari

  4. Machine Translation Pre-training for Data-to-Text Generation INLG, 2020 paper

    Mihir Kale; Scott Roy

  5. Fuzzy Temporal Protoforms for the Quantitative Description of Processes in Natural Language FUZZ-IEEE, 2021 paper

    Yago Fontenla-Seco; Alberto Bugarín; Manuel Lama

Training Methods

  1. Bootstrapping Generators from Noisy Data NAACL-HLT, 2018 paper

    Laura Perez-Beltrachini; Mirella Lapata

  2. DORB: Dynamically Optimizing Multiple Rewards with Bandits. EMNLP, 2020 paper

    Ramakanth Pasunuru; Han Guo; Mohit Bansal

  3. PARENTing via Model-Agnostic Reinforcement Learning to Correct Pathological Behaviors in Data-to-Text Generation. INLG, 2020 paper

    Clément Rebuffel; Laure Soulier; Geoffrey Scoutheeten; Patrick Gallinari

  4. Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learning EACL, 2021 paper

    Ernie Chang; Hui-Syuan Yeh; Vera Demberg

  5. On Training Instance Selection for Few-Shot Neural Text Generation ACL/IJCNLP, 2021 paper

    Ernie Chang; Xiaoyu Shen; Hui-Syuan Yeh; Vera Demberg

  6. Prefix-Tuning: Optimizing Continuous Prompts for Generation ACL/IJCNLP, 2021 paper

    Xiang Lisa Li; Percy Liang

Evaluation

  1. Evaluating the text quality, human likeness and tailoring component of PASS: A Dutch data-to-text system for soccer COLING, 2018 paper

    Chris van der Lee; Bart Verduijn; Emiel Krahmer; Sander Wubben

  2. Specificity Measures and Referential Success IEEE Transactions on Fuzzy Systems, 2018 paper

    Nicolas Marin; Gustavo Rivas-Gervilla; Daniel Sánchez; Ronald R. Yager

  3. Handling Divergent Reference Texts when Evaluating Table-to-Text Generation ACL, 2019 paper

    Bhuwan Dhingra; Manaal Faruqui; Ankur P. Parikh; Ming-Wei Chang; Dipanjan Das; William W. Cohen

  4. A Gold Standard Methodology for Evaluating Accuracy in Data-To-Text Systems arXiv, 2020 paper

    Craig Thomson; Ehud Reiter

  5. Evaluating Semantic Accuracy of Data-to-Text Generation with Natural Language Inference. INLG, 2020 paper

    Ondrej Dusek; Zdenek Kasner

  6. Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation EMNLP, 2021 paper

    Clément Rebuffel; Thomas Scialom; Laure Soulier; Benjamin Piwowarski; Sylvain Lamprier; Jacopo Staiano; Geoffrey Scoutheeten; Patrick Gallinari

  7. Entity-Based Semantic Adequacy for Data-to-Text Generation EMNLP (Findings), 2021 paper

    Juliette Faille; Albert Gatt; Claire Gardent

  8. Evaluation Guidelines to Deal with Implicit Phenomena to Assess Factuality in Data-to-Text Generation Proceedings of the 1st Workshop on Understanding Implicit and Underspecified Language, 2021 paper

    Roy Eisenstadt; Michael Elhadad

  9. Text-in-Context: Token-Level Error Detection for Table-to-Text Generation. INLG, 2021 paper

    Zdenek Kasner; Simon Mille; Ondrej Dusek

Applications

  1. Generating Syntactic Paraphrases EMNLP, 2018 paper

    Emilie Colin; Claire Gardent

  2. ESPRIT: Explaining Solutions to Physical Reasoning Tasks ACL, 2020 paper

    Nazneen Fatema Rajani; Rui Zhang; Yi Chern Tan; Stephan Zheng; Jeremy Weiss; Aadit Vyas; Abhijit Gupta; Caiming Xiong; Richard Socher; Dragomir R. Radev

  3. Fact-based Text Editing ACL, 2020 paper

    Hayate Iso; Chao Qiao; Hang Li

  4. Live Commenting of Football Games Using Machine Learning and Natural Language Generation thesis, 2020 paper

    Marcus Grönvall

  5. Towards a Dutch FrameNet lexicon and parser using the data-to-text method CLIN, 2020 paper

    Gosse Minnema; Levi Remijnse

  6. Unsupervised Pidgin Text Generation By Pivoting English Data and Self-Training. arXiv, 2020 paper

    Ernie Chang; David Ifeoluwa Adelani; Xiaoyu Shen; Vera Demberg

Thesis

  1. Neural generation of textual summaries from knowledge base triples thesis, 2019 link

    Pavlos Vougiouklis

  2. Automatic generation of anomaly reports in a Train Control System: Using Natural Language Generation and Case-Based Reasoning thesis, 2020 link

    Þórunn Ómarsdóttir

  3. Live Commenting of Football Games Using Machine Learning and Natural Language Generation thesis, 2020 link

    Marcus Grönvall

  4. Table-to-Text: Generating Descriptive Text for Scientific Tables from Randomized Controlled Trials thesis, 2020 link

    Qiang Wei

  5. Natural Language Generation : From Data Creation to Evaluation via Modelling thesis, 2021 link

    Anastasia Shimorina

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