mlsanityData to 7 Oct 2026

A Survey on Deep Learning Event Extraction: Approaches and Applications

arXiv 2107.02126 ↗First posted 5 Jul 2021cs.CLcited by 12

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Abstract (arXiv)

Event extraction (EE) is a crucial research task for promptly apprehending event information from massive textual data. With the rapid development of deep learning, EE based on deep learning technology has become a research hotspot. Numerous methods, datasets, and evaluation metrics have been proposed in the literature, raising the need for a comprehensive and updated survey. This article fills the research gap by reviewing the state-of-the-art approaches, especially focusing on the general domain EE based on deep learning models. We introduce a new literature classification of current general domain EE research according to the task definition. Afterward, we summarize the paradigm and models of EE approaches, and then discuss each of them in detail. As an important aspect, we summarize the benchmarks that support tests of predictions and evaluation metrics. A comprehensive comparison among different approaches is also provided in this survey. Finally, we conclude by summarizing future research directions facing the research area.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 85 of its 262 references that are in the map. First posted on arXiv 5 Jul 2021.

Builds on

85 of 262 references.

References · 85

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  4. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,861
  5. 2018Deep contextualized word representationscited by 2,285
  6. 2016Matching Networks for One Shot Learningcited by 2,246
  7. 2018Graph Convolutional Networks for Text Classificationcited by 345
  8. 2019Entity, Relation, and Event Extraction with Contextualized Span Representationscited by 261
  9. 2021A Comprehensive Survey on Graph Anomaly Detection with Deep Learningcited by 230
  10. 2019A Unified MRC Framework for Named Entity Recognitioncited by 199
  11. 2020Event Extraction by Answering (Almost) Natural Questionscited by 177
  12. 2021Document-Level Event Argument Extraction by Conditional Generationcited by 154
38 more
  1. 2020Named Entity Recognition as Dependency Parsingcited by 150
  2. 2021Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extractioncited by 129
  3. 2019Large-Scale Multi-Label Text Classification on EU Legislationcited by 104
  4. 2020MAVEN: A Massive General Domain Event Detection Datasetcited by 103
  5. 2019Entity-Relation Extraction as Multi-Turn Question Answeringcited by 96
  6. 2019ASER: A Large-scale Eventuality Knowledge Graphcited by 89
  7. 2020GLUCOSE: GeneraLized and COntextualized Story Explanationscited by 85
  8. 2018Event2Mind: Commonsense Inference on Events, Intents, and Reactionscited by 82
  9. 2018Chinese NER Using Lattice LSTMcited by 81
  10. 2019Multi-Sentence Argument Linkingcited by 80
  11. 2021SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanismcited by 75
  12. 2018Jointly Multiple Events Extraction via Attention-based Graph Information Aggregationcited by 73
  13. 2017Zero-Shot Transfer Learning for Event Extractioncited by 66
  14. 2021A Comprehensive Survey on Community Detection with Deep Learningcited by 63
  15. 2021LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classificationcited by 61
  16. 2020Cross-media Structured Common Space for Multimedia Event Extractioncited by 59
  17. 2019Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extractioncited by 54
  18. 2019Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detectioncited by 54
  19. 2020How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Contextcited by 53
  20. 2019Joint Event and Temporal Relation Extraction with Shared Representations and Structured Predictioncited by 52
  21. 2021Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNscited by 51
  22. 2016Joint Extraction of Events and Entities within a Document Contextcited by 48
  23. 2019Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolutioncited by 43
  24. 2020GATE: Graph Attention Transformer Encoder for Cross-lingual Relation and Event Extractioncited by 43
  25. 2020Deep Learning for Community Detection: Progress, Challenges and Opportunitiescited by 42
  26. 2020Adaptive Attentional Network for Few-Shot Knowledge Graph Completioncited by 42
  27. 2021Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extractioncited by 40
  28. 2018One for All: Neural Joint Modeling of Entities and Eventscited by 37
  29. 2021CLEVE: Contrastive Pre-training for Event Extractioncited by 36
  30. 2019Multi-Level Matching and Aggregation Network for Few-Shot Relation Classificationcited by 32
  31. 2020TriggerNER: Learning with Entity Triggers as Explanations for Named Entity Recognitioncited by 30
  32. 2021ESTER: A Machine Reading Comprehension Dataset for Event Semantic Relation Reasoningcited by 30
  33. 2020DeFormer: Decomposing Pre-trained Transformers for Faster Question Answeringcited by 29
  34. 2021Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Trackercited by 29
  35. 2020Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encodingcited by 28
  36. 2019Reading the Manual: Event Extraction as Definition Comprehensioncited by 26
  37. 2020Event-QA: A Dataset for Event-Centric Question Answering over Knowledge Graphscited by 26
  38. 2019A Structured Learning Approach to Temporal Relation Extractioncited by 24

50 most cited of 85 All 85 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 6; 2024: 3; 2025: 0; 2026: 1.

12 papers.

  1. 2024Artificial Intelligence for Literature Reviews: Opportunities and Challengescited by 30
  2. 2023Training Multimedia Event Extraction With Generated Images and Captionscited by 11
  3. 2022Information Extraction in Low-Resource Scenarios: Survey and Perspectivecited by 10
  4. 2024A Survey of Video Datasets for Grounded Event Understandingcited by 9
  5. 2023Easy-to-Hard Learning for Information Extractioncited by 5
  6. 2023Universal Information Extraction with Meta-Pretrained Self-Retrievalcited by 5
  7. 2022Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systemscited by 3
  8. 2023Heterogeneous Social Event Detection via Hyperbolic Graph Representationscited by 3
  9. 2023A Monte Carlo Language Model Pipeline for Zero-Shot Sociopolitical Event Extractioncited by 2
  10. 2023Unbiased and Efficient Self-Supervised Incremental Contrastive Learningcited by 1
  11. 2026QO-Bench: Diagnosing Query-Operator-Preserving Retrieval over Typed Event Tuplescited by 1
  12. 2024Multi-layer Sequence Labeling-based Joint Biomedical Event Extractioncited by 0