mlsanityData to 7 Oct 2026

EntSUM: A Data Set for Entity-Centric Summarization

arXiv 2204.02213 ↗First posted 5 Apr 2022cs.CLcited by 22

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Abstract (arXiv)

Controllable summarization aims to provide summaries that take into account user-specified aspects and preferences to better assist them with their information need, as opposed to the standard summarization setup which build a single generic summary of a document. We introduce a human-annotated data set EntSUM for controllable summarization with a focus on named entities as the aspects to control. We conduct an extensive quantitative analysis to motivate the task of entity-centric summarization and show that existing methods for controllable summarization fail to generate entity-centric summaries. We propose extensions to state-of-the-art summarization approaches that achieve substantially better results on our data set. Our analysis and results show the challenging nature of this task and of the proposed data set.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 25 of its 45 references that are in the map. First posted on arXiv 5 Apr 2022.

Builds on

25 of 45 references.

References · 25

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  4. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  5. 2019fairseq: A Fast, Extensible Toolkit for Sequence Modelingcited by 1,486
  6. 2018Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationcited by 1,308
  7. 2015Teaching Machines to Read and Comprehendcited by 1,039
  8. 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 832
  9. 2019Text Summarization with Pretrained Encoderscited by 553
  10. 2018Generating Wikipedia by Summarizing Long Sequencescited by 333
  11. 2016SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documentscited by 245
  12. 2020TLDR: Extreme Summarization of Scientific Documentscited by 136
13 more
  1. 2020GSum: A General Framework for Guided Neural Abstractive Summarizationcited by 129
  2. 2017Controllable Abstractive Summarizationcited by 110
  3. 2020CTRLsum: Towards Generic Controllable Text Summarizationcited by 98
  4. 2020Extractive Opinion Summarization in Quantized Transformer Spacescited by 76
  5. 2016Controlling Output Length in Neural Encoder-Decoderscited by 75
  6. 2018Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervisedcited by 75
  7. 2018Content Selection in Deep Learning Models of Summarizationcited by 64
  8. 2021Aspect-Controllable Opinion Summarizationcited by 47
  9. 2019Informative and Controllable Opinion Summarizationcited by 27
  10. 2020Abstractive Summarization with Combination of Pre-trained Sequence-to-Sequence and Saliency Modelscited by 15
  11. 2021Decision-Focused Summarizationcited by 11
  12. 2021iFacetSum: Coreference-based Interactive Faceted Summarization for Multi-Document Explorationcited by 8
  13. 2021Subjective Bias in Abstractive Summarizationcited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 4; 2023: 6; 2024: 8; 2025: 3; 2026: 1.

22 papers.

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  1. 2024A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methodscited by 101
  2. 2023From Sparse to Dense: GPT-4 Summarization with Chain of Density Promptingcited by 52
  3. 2023Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects -- A Surveycited by 18
  4. 2022MACSum: Controllable Summarization with Mixed Attributescited by 13
  5. 2023NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarizationcited by 13
  6. 2024Can Large Language Model Summarizers Adapt to Diverse Scientific Communication Goals?cited by 6
  7. 2025GUM-SAGE: A Novel Dataset and Approach for Graded Entity Salience Predictioncited by 6
  8. 2022Why Do You Feel This Way? Summarizing Triggers of Emotions in Social Media Postscited by 5
  9. 2024GUMsley: Evaluating Entity Salience in Summarization for 12 English Genrescited by 5
  10. 2024Disordered-DABS: A Benchmark for Dynamic Aspect-Based Summarization in Disordered Textscited by 5
  11. 2024MODABS: Multi-Objective Learning for Dynamic Aspect-Based Summarizationcited by 3
  12. 2024BookWorm: A Dataset for Character Description and Analysiscited by 3
10 more
  1. 2026Author-in-the-Loop Response Generation and Evaluation: Integrating Author Expertise and Intent in Responses to Peer Reviewcited by 3
  2. 2022Attend to the Right Context: A Plug-and-Play Module for Content-Controllable Summarizationcited by 2
  3. 2023GUMSum: Multi-Genre Data and Evaluation for English Abstractive Summarizationcited by 2
  4. 2023Leveraging Contextual Information for Effective Entity Salience Detectioncited by 2
  5. 2025Adaptive Planning for Multi-Attribute Controllable Summarization with Monte Carlo Tree Searchcited by 2
  6. 2023Controllable Topic-Focused Abstractive Summarizationcited by 1
  7. 2024Scalable Detection of Salient Entities in News Articlescited by 1
  8. 2024Exploring Iterative Controllable Summarization with Large Language Modelscited by 1
  9. 2022Topic-Controllable Summarization: Topic-Aware Evaluation and Transformer Methodscited by 0
  10. 2025CARPAS: Towards Content-Aware Refinement of Provided Aspects for Summarization in Large Language Modelscited by 0