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Data-to-Text Generation with Content Selection and Planning

arXiv 1809.00582 ↗First posted 3 Sep 2018cs.CLcited by 106

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Abstract (arXiv)

Recent advances in data-to-text generation have led to the use of large-scale datasets and neural network models which are trained end-to-end, without explicitly modeling what to say and in what order. In this work, we present a neural network architecture which incorporates content selection and planning without sacrificing end-to-end training. We decompose the generation task into two stages. Given a corpus of data records (paired with descriptive documents), we first generate a content plan highlighting which information should be mentioned and in which order and then generate the document while taking the content plan into account. Automatic and human-based evaluation experiments show that our model outperforms strong baselines improving the state-of-the-art on the recently released RotoWire dataset.

Key facts. Cited by 106 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Sep 2018.

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Citing papers per year: 2021: 30; 2022: 21; 2023: 23; 2024: 17; 2025: 8; 2026: 7.

106 papers.

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  1. 2022Survey of Hallucination in Natural Language Generationcited by 2,075
  2. 2022Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Textcited by 155
  3. 2022A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Modelscited by 129
  4. 2021Planning with Learned Entity Prompts for Abstractive Summarizationcited by 75
  5. 2021Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Featurescited by 74
  6. 2021Plan-then-Generate: Controlled Data-to-Text Generation via Planningcited by 52
  7. 2021Text-to-Table: A New Way of Information Extractioncited by 47
  8. 2022Conditional Generation with a Question-Answering Blueprintcited by 44
  9. 2021Controlling Hallucinations at Word Level in Data-to-Text Generationcited by 41
  10. 2021IndicBART: A Pre-trained Model for Indic Natural Language Generationcited by 39
  11. 2021Data-to-text Generation with Macro Planningcited by 34
  12. 2021Does Pretraining for Summarization Require Knowledge Transfer?cited by 30
38 more
  1. 2024Learning to Plan and Generate Text with Citationscited by 28
  2. 2021Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric Viewcited by 24
  3. 2021Learning to Complete Code with Sketchescited by 23
  4. 2021TSQA: Tabular Scenario Based Question Answeringcited by 21
  5. 2021Sketch and Refine: Towards Faithful and Informative Table-to-Text Generationcited by 21
  6. 2021Few-Shot Table-to-Text Generation with Prototype Memorycited by 21
  7. 2022Neural Pipeline for Zero-Shot Data-to-Text Generationcited by 19
  8. 2021Self-Supervised Multimodal Opinion Summarizationcited by 18
  9. 2022Language modeling via stochastic processescited by 18
  10. 2022Data-to-text Generation with Variational Sequential Planningcited by 17
  11. 2022PLOG: Table-to-Logic Pretraining for Logical Table-to-Text Generationcited by 16
  12. 2024Beyond Traditional Benchmarks: Analyzing Behaviors of Open LLMs on Data-to-Text Generationcited by 16
  13. 2022ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Modelscited by 14
  14. 2023Dialogue Planning via Brownian Bridge Stochastic Process for Goal-directed Proactive Dialoguecited by 14
  15. 2024LitLLMs, LLMs for Literature Review: Are we there yet?cited by 14
  16. 2021AutoChart: A Dataset for Chart-to-Text Generation Taskcited by 13
  17. 2023CLEVA: Chinese Language Models EVAluation Platformcited by 13
  18. 2023SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pagescited by 12
  19. 2023Affective and Dynamic Beam Search for Story Generationcited by 12
  20. 2021Stage-wise Fine-tuning for Graph-to-Text Generationcited by 11
  21. 2024GraphXAIN: Narratives to Explain Graph Neural Networkscited by 11
  22. 2021Constrained Text Generation with Global Guidance -- Case Study on CommonGencited by 10
  23. 2022Innovations in Neural Data-to-text Generation: A Surveycited by 10
  24. 2021Generation Challenges: Results of the Accuracy Evaluation Shared Taskcited by 9
  25. 2021Biomedical Data-to-Text Generation via Fine-Tuning Transformerscited by 9
  26. 2023Text-Blueprint: An Interactive Platform for Plan-based Conditional Generationcited by 9
  27. 2023Unified Text Structuralization with Instruction-tuned Language Modelscited by 8
  28. 2023Expository Text Generation: Imitate, Retrieve, Paraphrasecited by 8
  29. 2021AGGGEN: Ordering and Aggregating while Generatingcited by 7
  30. 2022Generating Full Length Wikipedia Biographies: The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographiescited by 7
  31. 2022MURMUR: Modular Multi-Step Reasoning for Semi-Structured Data-to-Text Generationcited by 7
  32. 2023μPLAN: Summarizing using a Content Plan as Cross-Lingual Bridgecited by 7
  33. 2024Hierarchical Indexing for Retrieval-Augmented Opinion Summarizationcited by 7
  34. 2024Can LLMs "Reason" in Music? An Evaluation of LLMs' Capability of Music Understanding and Generationcited by 7
  35. 2021Set-to-Sequence Methods in Machine Learning: a Reviewcited by 6
  36. 2023Improving User Controlled Table-To-Text Generation Robustnesscited by 6
  37. 2024Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive Dialoguecited by 6
  38. 2024Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directionscited by 6

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