mlsanityData to 7 Oct 2026

A Neural Attention Model for Abstractive Sentence Summarization

arXiv 1509.00685 ↗First posted 2 Sep 2015cs.CL cs.AIcited by 394

Not on the map. Why?

Abstract (arXiv)

Summarization based on text extraction is inherently limited, but generation-style abstractive methods have proven challenging to build. In this work, we propose a fully data-driven approach to abstractive sentence summarization. Our method utilizes a local attention-based model that generates each word of the summary conditioned on the input sentence. While the model is structurally simple, it can easily be trained end-to-end and scales to a large amount of training data. The model shows significant performance gains on the DUC-2004 shared task compared with several strong baselines.

Key facts. Cited by 394 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Sep 2015.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2020: 3; 2021: 124; 2022: 109; 2023: 68; 2024: 40; 2025: 37; 2026: 13.

394 papers.

Sort:

By area:

  1. 2020Learning to summarize from human feedbackcited by 2,562
  2. 2023A Survey of Large Language Modelscited by 2,537
  3. 2021GLM: General Language Model Pretraining with Autoregressive Blank Infillingcited by 1,026
  4. 2022OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Frameworkcited by 742
  5. 2023Benchmarking Large Language Models for News Summarizationcited by 444
  6. 2022Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Taskscited by 420
  7. 2021QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarizationcited by 363
  8. 2021XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languagescited by 346
  9. 2023Formalizing and Benchmarking Prompt Injection Attacks and Defensescited by 328
  10. 2022News Summarization and Evaluation in the Era of GPT-3cited by 324
  11. 2021Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metricscited by 285
  12. 2021SPoT: Better Frozen Model Adaptation through Soft Prompt Transfercited by 235
38 more
  1. 2024Generative Representational Instruction Tuningcited by 227
  2. 2021Want To Reduce Labeling Cost? GPT-3 Can Helpcited by 196
  3. 2021ExT5: Towards Extreme Multi-Task Scaling for Transfer Learningcited by 161
  4. 2022BRIO: Bringing Order to Abstractive Summarizationcited by 161
  5. 2022Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Textcited by 154
  6. 2023mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Videocited by 154
  7. 2025DataSentinel: A Game-Theoretic Detection of Prompt Injection Attackscited by 124
  8. 2024Automatic and Universal Prompt Injection Attacks against Large Language Modelscited by 112
  9. 2022Task-aware Retrieval with Instructionscited by 107
  10. 2024A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methodscited by 101
  11. 2021Efficient Nearest Neighbor Language Modelscited by 93
  12. 2025A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applicationscited by 91
  13. 2022On Decoding Strategies for Neural Text Generatorscited by 89
  14. 2023On the Possibilities of AI-Generated Text Detectioncited by 88
  15. 2021SummScreen: A Dataset for Abstractive Screenplay Summarizationcited by 80
  16. 2022Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoisecited by 79
  17. 2021Improving Faithfulness in Abstractive Summarization with Contrast Candidate Generation and Selectioncited by 75
  18. 2022An Empirical Survey on Long Document Summarization: Datasets, Models and Metricscited by 74
  19. 2020Autoregressive Knowledge Distillation through Imitation Learningcited by 68
  20. 2021DOC2PPT: Automatic Presentation Slides Generation from Scientific Documentscited by 68
  21. 2023AI-Generated Content (AIGC): A Surveycited by 59
  22. 2021Improving Factual Consistency of Abstractive Summarization via Question Answeringcited by 55
  23. 2022Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decodingcited by 54
  24. 2021A Survey on Green Deep Learningcited by 52
  25. 2024A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Modelscited by 52
  26. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 50
  27. 2021ExplainaBoard: An Explainable Leaderboard for NLPcited by 50
  28. 2021Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarizationcited by 50
  29. 2023DINOISER: Diffused Conditional Sequence Learning by Manipulating Noisescited by 50
  30. 2022FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarizationcited by 49
  31. 2022CoditT5: Pretraining for Source Code and Natural Language Editingcited by 45
  32. 2021SelfExplain: A Self-Explaining Architecture for Neural Text Classifierscited by 44
  33. 2023Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decodercited by 44
  34. 2021Generate, Annotate, and Learn: NLP with Synthetic Textcited by 42
  35. 2022IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languagescited by 42
  36. 2022Neural Approaches to Conversational Information Retrievalcited by 41
  37. 2022Empowering Diffusion Models on the Embedding Space for Text Generationcited by 40
  38. 2022How Large Language Models are Transforming Machine-Paraphrased Plagiarismcited by 38

50 most cited of 394 All 394 (JSON)