mlsanityData to 14 Oct 2026

Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects -- A Survey

arXiv 2311.09212 ↗First posted 15 Nov 2023cs.CL cs.AIcited by 18

Not on the map. Why?

Abstract (arXiv)

Generic text summarization approaches often fail to address the specific intent and needs of individual users. Recently, scholarly attention has turned to the development of summarization methods that are more closely tailored and controlled to align with specific objectives and user needs. Despite a growing corpus of controllable summarization research, there is no comprehensive survey available that thoroughly explores the diverse controllable attributes employed in this context, delves into the associated challenges, and investigates the existing solutions. In this survey, we formalize the Controllable Text Summarization (CTS) task, categorize controllable attributes according to their shared characteristics and objectives, and present a thorough examination of existing datasets and methods within each category. Moreover, based on our findings, we uncover limitations and research gaps, while also exploring potential solutions and future directions for CTS. We release our detailed analysis of CTS papers at https://github.com/ashokurlana/controllable_text_summarization_survey.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). Builds on 76 of its 123 references that are in the map. First posted on arXiv 15 Nov 2023.

Builds on

76 of 123 references.

References · 76

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  5. 2017A Unified Approach to Interpreting Model Predictionscited by 6,555
  6. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  7. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  8. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,548
  9. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,057
  10. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,915
  11. 2020Longformer: The Long-Document Transformercited by 3,413
  12. 2017Axiomatic Attribution for Deep Networkscited by 3,384
38 more
  1. 2018Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationcited by 1,317
  2. 2017Get To The Point: Summarization with Pointer-Generator Networkscited by 1,292
  3. 2015Effective Approaches to Attention-based Neural Machine Translationcited by 1,026
  4. 2016Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyondcited by 812
  5. 2020Quantifying Attention Flow in Transformerscited by 775
  6. 2021BARTScore: Evaluating Generated Text as Text Generationcited by 722
  7. 2019Text Summarization with Pretrained Encoderscited by 556
  8. 2019SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarizationcited by 535
  9. 2018Universal Sentence Encodercited by 489
  10. 2015A Neural Attention Model for Abstractive Sentence Summarizationcited by 396
  11. 2021QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarizationcited by 365
  12. 2016SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documentscited by 246
  13. 2020GSum: A General Framework for Guided Neural Abstractive Summarizationcited by 129
  14. 2017Controllable Abstractive Summarizationcited by 110
  15. 2019Answers Unite! Unsupervised Metrics for Reinforced Summarization Modelscited by 92
  16. 2020Fill in the BLANC: Human-free quality estimation of document summariescited by 82
  17. 2019Comparison of Diverse Decoding Methods from Conditional Language Modelscited by 78
  18. 2020Extractive Opinion Summarization in Quantized Transformer Spacescited by 76
  19. 2016Controlling Output Length in Neural Encoder-Decoderscited by 75
  20. 2018Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervisedcited by 75
  21. 2021Planning with Learned Entity Prompts for Abstractive Summarizationcited by 75
  22. 2020SUPERT: Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document Summarizationcited by 69
  23. 2015Better Summarization Evaluation with Word Embeddings for ROUGEcited by 66
  24. 2017Text Summarization Techniques: A Brief Surveycited by 59
  25. 2016A Simple, Fast Diverse Decoding Algorithm for Neural Generationcited by 58
  26. 2019Positional Encoding to Control Output Sequence Lengthcited by 56
  27. 2020WikiAsp: A Dataset for Multi-domain Aspect-based Summarizationcited by 56
  28. 2020Exploring Controllable Text Generation Techniquescited by 55
  29. 2021Aspect-Controllable Opinion Summarizationcited by 47
  30. 2020Hooks in the Headline: Learning to Generate Headlines with Controlled Stylescited by 46
  31. 2022A Causal Lens for Controllable Text Generationcited by 45
  32. 2018Importance of Search and Evaluation Strategies in Neural Dialogue Modelingcited by 44
  33. 2021Finding a Balanced Degree of Automation for Summary Evaluationcited by 43
  34. 2021MReD: A Meta-Review Dataset for Structure-Controllable Text Generationcited by 42
  35. 2022A Survey on Cross-Lingual Summarizationcited by 38
  36. 2020OpinionDigest: A Simple Framework for Opinion Summarizationcited by 37
  37. 2021ASPECTNEWS: Aspect-Oriented Summarization of News Documentscited by 37
  38. 2021Controllable Neural Dialogue Summarization with Personal Named Entity Planningcited by 36

50 most cited of 76 All 76 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 7; 2025: 4; 2026: 7.

18 papers.

Sort:

By area:

  1. 2025Understanding (Un)Reliability of Steering Vectors in Language Modelscited by 47
  2. 2024LimGen: Probing the LLMs for Generating Suggestive Limitations of Research Paperscited by 16
  3. 2024Zero-Shot Strategies for Length-Controllable Summarizationcited by 10
  4. 2024PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Modelscited by 5
  5. 2026STRUCTSURVEY: Structured Agentic Retrieval for Automated Survey Paper Generationcited by 4
  6. 2024No Size Fits All: The Perils and Pitfalls of Leveraging LLMs Vary with Company Sizecited by 3
  7. 2024DiscoGraMS: Enhancing Movie Screen-Play Summarization using Movie Character-Aware Discourse Graphcited by 2
  8. 2025Beyond Multiple Choice: Evaluating Steering Vectors for Summarizationcited by 2
  9. 2025Adaptive Planning for Multi-Attribute Controllable Summarization with Monte Carlo Tree Searchcited by 2
  10. 2024Exploring Iterative Controllable Summarization with Large Language Modelscited by 1
  11. 2026Position: Natural Language Should Not Fully Replace Formal Languagescited by 1
  12. 2026SWIM: Student Writing Simulation via Proficiency-Conditioned Generationcited by 1
6 more
  1. 2024CCSBench: Evaluating Compositional Controllability in LLMs for Scientific Document Summarizationcited by 0
  2. 2025Towards Personalized Explanations for Health Simulations: A Mixed-Methods Framework for Stakeholder-Centric Summarizationcited by 0
  3. 2026LogicEval: A Systematic Framework for Evaluating Automated Repair Techniques for Logical Vulnerabilities in Real-World Softwarecited by 0
  4. 2026No Reader Left Behind: Multi-Agent Summaries Everyone Can Understandcited by 0
  5. 2026Summarization is Not Dead Yetcited by 0
  6. 2026Controlled Attribute-Specific Summarization of Interrogative Dialoguescited by 0