mlsanityData to 7 Oct 2026

A comprehensive review of automatic text summarization techniques: method, data, evaluation and coding

arXiv 2301.03403 ↗First posted 4 Jan 2023cs.CL cs.LGcited by 4

Not on the map. Why?

Abstract (arXiv)

We provide a literature review about Automatic Text Summarization (ATS) systems. We consider a citation-based approach. We start with some popular and well-known papers that we have in hand about each topic we want to cover and we have tracked the "backward citations" (papers that are cited by the set of papers we knew beforehand) and the "forward citations" (newer papers that cite the set of papers we knew beforehand). In order to organize the different methods, we present the diverse approaches to ATS guided by the mechanisms they use to generate a summary. Besides presenting the methods, we also present an extensive review of the datasets available for summarization tasks and the methods used to evaluate the quality of the summaries. Finally, we present an empirical exploration of these methods using the CNN Corpus dataset that provides golden summaries for extractive and abstractive methods.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 72 of its 347 references that are in the map. First posted on arXiv 4 Jan 2023.

Builds on

72 of 347 references.

References · 72

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  5. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  6. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  7. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
  8. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,243
  9. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,016
  10. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
  11. 2020Longformer: The Long-Document Transformercited by 3,362
  12. 2021Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsitycited by 3,014
38 more
  1. 2014Sequence to Sequence Learning with Neural Networkscited by 2,974
  2. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
  3. 2018Deep contextualized word representationscited by 2,285
  4. 2018Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationcited by 1,308
  5. 2019A Comprehensive Survey on Transfer Learningcited by 1,154
  6. 2019PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarizationcited by 1,100
  7. 2015Teaching Machines to Read and Comprehendcited by 1,039
  8. 2016Bag of Tricks for Efficient Text Classificationcited by 869
  9. 2019Unified Language Model Pre-training for Natural Language Understanding and Generationcited by 668
  10. 2019Text Summarization with Pretrained Encoderscited by 553
  11. 2019SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarizationcited by 530
  12. 2018A Discourse-Aware Attention Model for Abstractive Summarization of Long Documentscited by 477
  13. 2019Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Modelcited by 431
  14. 2019MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distancecited by 415
  15. 2021A Survey of Data Augmentation Approaches for NLPcited by 408
  16. 2020A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospectscited by 396
  17. 2021XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languagescited by 346
  18. 2019MASS: Masked Sequence to Sequence Pre-training for Language Generationcited by 345
  19. 2021Efficient Attentions for Long Document Summarizationcited by 342
  20. 2018Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategiescited by 292
  21. 2016SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documentscited by 245
  22. 2020ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-trainingcited by 221
  23. 2020UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Trainingcited by 204
  24. 2018WikiHow: A Large Scale Text Summarization Datasetcited by 203
  25. 2015A Neural Conversational Modelcited by 195
  26. 2019BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarizationcited by 155
  27. 2018Ranking Sentences for Extractive Summarization with Reinforcement Learningcited by 128
  28. 2019BillSum: A Corpus for Automatic Summarization of US Legislationcited by 117
  29. 2016Neural Summarization by Extracting Sentences and Wordscited by 114
  30. 2017Learned in Translation: Contextualized Word Vectorscited by 104
  31. 2018Abstractive Summarization of Reddit Posts with Multi-level Memory Networkscited by 102
  32. 2021An Empirical Survey of Data Augmentation for Limited Data Learning in NLPcited by 101
  33. 2021Pretrained Language Models for Text Generation: A Surveycited by 95
  34. 2019Answers Unite! Unsupervised Metrics for Reinforced Summarization Modelscited by 92
  35. 2020Fill in the BLANC: Human-free quality estimation of document summariescited by 80
  36. 2019ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networkscited by 73
  37. 2020SUPERT: Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document Summarizationcited by 69
  38. 2015Better Summarization Evaluation with Word Embeddings for ROUGEcited by 66

50 most cited of 72 All 72 (JSON)

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 2; 2025: 1.

4 papers.

  1. 2024A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Modelscited by 52
  2. 2023Hybrid Long Document Summarization using C2F-FAR and ChatGPT: A Practical Studycited by 5
  3. 2024The State and Fate of Summarization Datasets: A Surveycited by 3
  4. 2025BOE-XSUM: Extreme Summarization in Clear Language of Spanish Legal Decrees and Notificationscited by 0