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A Survey of Knowledge-Enhanced Text Generation

arXiv 2010.04389 ↗First posted 9 Oct 2020cs.CL cs.AI cs.LGcited by 119

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Abstract (arXiv)

The goal of text generation is to make machines express in human language. It is one of the most important yet challenging tasks in natural language processing (NLP). Since 2014, various neural encoder-decoder models pioneered by Seq2Seq have been proposed to achieve the goal by learning to map input text to output text. However, the input text alone often provides limited knowledge to generate the desired output, so the performance of text generation is still far from satisfaction in many real-world scenarios. To address this issue, researchers have considered incorporating various forms of knowledge beyond the input text into the generation models. This research direction is known as knowledge-enhanced text generation. In this survey, we present a comprehensive review of the research on knowledge enhanced text generation over the past five years. The main content includes two parts: (i) general methods and architectures for integrating knowledge into text generation; (ii) specific techniques and applications according to different forms of knowledge data. This survey can have broad audiences, researchers and practitioners, in academia and industry.

Key facts. Cited by 119 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Oct 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 31; 2023: 33; 2024: 28; 2025: 11; 2026: 3.

119 papers.

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  1. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  2. 2021Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Surveycited by 457
  3. 2022Generate rather than Retrieve: Large Language Models are Strong Context Generatorscited by 296
  4. 2023ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddingscited by 238
  5. 2022Factuality Enhanced Language Models for Open-Ended Text Generationcited by 200
  6. 2023Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Modelscited by 180
  7. 2023Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMscited by 175
  8. 2023Can LLM-Generated Misinformation Be Detected?cited by 173
  9. 2022Deep Bidirectional Language-Knowledge Graph Pretrainingcited by 156
  10. 2023Factuality Challenges in the Era of Large Language Modelscited by 125
  11. 2023On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligencecited by 88
  12. 2023Improving Language Models via Plug-and-Play Retrieval Feedbackcited by 87
38 more
  1. 2023Cognitive Mirage: A Review of Hallucinations in Large Language Modelscited by 83
  2. 2022Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Surveycited by 80
  3. 2024A Survey on Retrieval-Augmented Text Generation for Large Language Modelscited by 77
  4. 2022A Survey of Knowledge Enhanced Pre-trained Language Modelscited by 76
  5. 2024StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurizationcited by 70
  6. 2022Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversationcited by 56
  7. 2023Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modelingcited by 56
  8. 2024KG-RAG: Bridging the Gap Between Knowledge and Creativitycited by 55
  9. 2023TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usagecited by 54
  10. 2021Complex Knowledge Base Question Answering: A Surveycited by 52
  11. 2025Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Abovecited by 51
  12. 2022RHO (ρ): Reducing Hallucination in Open-domain Dialogues with Knowledge Groundingcited by 47
  13. 2022A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methodscited by 42
  14. 2021Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attentioncited by 40
  15. 2021Dict-BERT: Enhancing Language Model Pre-training with Dictionarycited by 38
  16. 2021Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AIcited by 38
  17. 2023Merging Generated and Retrieved Knowledge for Open-Domain QAcited by 36
  18. 2024LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Modelcited by 34
  19. 2023How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advancescited by 33
  20. 2023Say What You Mean! Large Language Models Speak Too Positively about Negative Commonsense Knowledgecited by 32
  21. 2021Relational World Knowledge Representation in Contextual Language Models: A Reviewcited by 31
  22. 2023Trends in Integration of Knowledge and Large Language Models: A Survey and Taxonomy of Methods, Benchmarks, and Applicationscited by 28
  23. 2024Is Table Retrieval a Solved Problem? Exploring Join-Aware Multi-Table Retrievalcited by 27
  24. 2023Large Language Models are Built-in Autoregressive Search Enginescited by 26
  25. 2023IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositionscited by 25
  26. 2022Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answeringcited by 22
  27. 2022Open-world Story Generation with Structured Knowledge Enhancement: A Comprehensive Surveycited by 21
  28. 2023A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraintscited by 21
  29. 2024MINTQA: A Multi-Hop Question Answering Benchmark for Evaluating LLMs on New and Tail Knowledgecited by 20
  30. 2021Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representationscited by 19
  31. 2022Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Expertscited by 19
  32. 2022UnifieR: A Unified Retriever for Large-Scale Retrievalcited by 19
  33. 2021Retrieval Enhanced Model for Commonsense Generationcited by 18
  34. 2023User Modeling in the Era of Large Language Models: Current Research and Future Directionscited by 18
  35. 2024Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challengescited by 18
  36. 2024Compressing Long Context for Enhancing RAG with AMR-based Concept Distillationcited by 16
  37. 2025RAS: Retrieval-And-Structuring for Knowledge-Intensive LLM Generationcited by 16
  38. 2022UniSumm and SummZoo: Unified Model and Diverse Benchmark for Few-Shot Summarizationcited by 15

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