mlsanityData to 7 Oct 2026

From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Survey

arXiv 2305.02579 ↗First posted 4 May 2023cs.CL cs.AIcited by 14

Not on the map. Why?

Abstract (arXiv)

Keyphrase prediction aims to generate phrases (keyphrases) that highly summarizes a given document. Recently, researchers have conducted in-depth studies on this task from various perspectives. In this paper, we comprehensively summarize representative studies from the perspectives of dominant models, datasets and evaluation metrics. Our work analyzes up to 167 previous works, achieving greater coverage of this task than previous surveys. Particularly, we focus highly on deep learning-based keyphrase prediction, which attracts increasing attention of this task in recent years. Afterwards, we conduct several groups of experiments to carefully compare representative models. To the best of our knowledge, our work is the first attempt to compare these models using the identical commonly-used datasets and evaluation metric, facilitating in-depth analyses of their disadvantages and advantages. Finally, we discuss the possible research directions of this task in the future.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 73 of its 173 references that are in the map. First posted on arXiv 4 May 2023.

Builds on

73 of 173 references.

References · 73

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  2. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  3. 2020Longformer: The Long-Document Transformercited by 3,362
  4. 2018Deep contextualized word representationscited by 2,285
  5. 2020MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformerscited by 1,414
  6. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,404
  7. 2014Distributed Representations of Sentences and Documentscited by 677
  8. 2019Unified Language Model Pre-training for Natural Language Understanding and Generationcited by 668
  9. 2019ERNIE: Enhanced Language Representation with Informative Entitiescited by 525
  10. 2016Incorporating Copying Mechanism in Sequence-to-Sequence Learningcited by 217
  11. 2018RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systemscited by 136
  12. 2016Modeling Coverage for Neural Machine Translationcited by 110
38 more
  1. 2017Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Featurescited by 103
  2. 2017Deep Keyphrase Generationcited by 102
  3. 2018Multi-Reward Reinforced Summarization with Saliency and Entailmentcited by 73
  4. 2018One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrasescited by 52
  5. 2018Unsupervised Keyphrase Extraction with Multipartite Graphscited by 50
  6. 2018Keyphrase Generation with Correlation Constraintscited by 45
  7. 2019Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewardscited by 41
  8. 2019KPTimes: A Large-Scale Dataset for Keyphrase Generation on News Documentscited by 41
  9. 2021One2Set: Generating Diverse Keyphrases as a Setcited by 41
  10. 2020Exclusive Hierarchical Decoding for Deep Keyphrase Generationcited by 38
  11. 2018Semi-Supervised Learning for Neural Keyphrase Generationcited by 36
  12. 2018Title-Guided Encoding for Keyphrase Generationcited by 36
  13. 2021Learning Rich Representation of Keyphrases from Textcited by 36
  14. 2018Entity-Duet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrievalcited by 33
  15. 2019Topic-Aware Neural Keyphrase Generation for Social Media Languagecited by 33
  16. 2019An Integrated Approach for Keyphrase Generation via Exploring the Power of Retrieval and Extractioncited by 28
  17. 2019Open Domain Web Keyphrase Extraction Beyond Language Modelingcited by 28
  18. 2020An Empirical Study on Neural Keyphrase Generationcited by 25
  19. 2017Scientific Information Extraction with Semi-supervised Neural Taggingcited by 24
  20. 2020Select, Extract and Generate: Neural Keyphrase Generation with Layer-wise Coverage Attentioncited by 24
  21. 2021Keyphrase Generation for Scientific Document Retrievalcited by 23
  22. 2021MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extractioncited by 20
  23. 2020Capturing Global Informativeness in Open Domain Keyphrase Extractioncited by 17
  24. 2021Unsupervised Keyphrase Extraction by Jointly Modeling Local and Global Contextcited by 17
  25. 2019DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrasescited by 16
  26. 2021Importance Estimation from Multiple Perspectives for Keyphrase Extractioncited by 16
  27. 2021UniKeyphrase: A Unified Extraction and Generation Framework for Keyphrase Predictioncited by 15
  28. 2021Heterogeneous Graph Neural Networks for Keyphrase Generationcited by 15
  29. 2019Keyphrase Extraction from Scholarly Articles as Sequence Labeling using Contextualized Embeddingscited by 14
  30. 2021UCPhrase: Unsupervised Context-aware Quality Phrase Taggingcited by 14
  31. 2022Representation Learning for Resource-Constrained Keyphrase Generationcited by 14
  32. 2021Keyphrase Generation with Fine-Grained Evaluation-Guided Reinforcement Learningcited by 13
  33. 2022Applying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generationcited by 13
  34. 2022LDKP: A Dataset for Identifying Keyphrases from Long Scientific Documentscited by 13
  35. 2022WR-ONE2SET: Towards Well-Calibrated Keyphrase Generationcited by 13
  36. 2019Keyphrase Extraction from Disaster-related Tweetscited by 12
  37. 2021Keyphrase Generation Beyond the Boundaries of Title and Abstractcited by 12
  38. 2020Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image Wordingscited by 11

50 most cited of 73 All 73 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 6; 2025: 4; 2026: 2.

14 papers.

Sort: