mlsanityData to 14 Oct 2026

NEWTS: A Corpus for News Topic-Focused Summarization

arXiv 2205.15661 ↗First posted 31 May 2022cs.CLcited by 27

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Abstract (arXiv)

Text summarization models are approaching human levels of fidelity. Existing benchmarking corpora provide concordant pairs of full and abridged versions of Web, news or, professional content. To date, all summarization datasets operate under a one-size-fits-all paradigm that may not reflect the full range of organic summarization needs. Several recently proposed models (e.g., plug and play language models) have the capacity to condition the generated summaries on a desired range of themes. These capacities remain largely unused and unevaluated as there is no dedicated dataset that would support the task of topic-focused summarization. This paper introduces the first topical summarization corpus NEWTS, based on the well-known CNN/Dailymail dataset, and annotated via online crowd-sourcing. Each source article is paired with two reference summaries, each focusing on a different theme of the source document. We evaluate a representative range of existing techniques and analyze the effectiveness of different prompting methods.

Key facts. Cited by 27 papers in the map (data through 14 Oct 2026). Builds on 22 of its 29 references that are in the map. First posted on arXiv 31 May 2022.

Builds on

22 of 29 references.

References · 22

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10 more
  1. 2017Controllable Abstractive Summarizationcited by 110
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 4; 2023: 9; 2024: 6; 2025: 5; 2026: 3.

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  1. 2023Exploring the Limits of ChatGPT for Query or Aspect-based Text Summarizationcited by 122
  2. 2024A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methodscited by 102
  3. 2023SummIt: Iterative Text Summarization via ChatGPTcited by 54
  4. 2024A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Modelscited by 52
  5. 2025Understanding (Un)Reliability of Steering Vectors in Language Modelscited by 47
  6. 2022Prompted Opinion Summarization with GPT-3.5cited by 44
  7. 2022OASum: Large-Scale Open Domain Aspect-based Summarizationcited by 24
  8. 2025Enhancing Retrieval-Augmented Generation: A Study of Best Practicescited by 23
  9. 2023Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects -- A Surveycited by 18
  10. 2023ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?cited by 15
  11. 2023LMGQS: A Large-scale Dataset for Query-focused Summarizationcited by 9
  12. 2024LexAbSumm: Aspect-based Summarization of Legal Decisionscited by 9
15 more
  1. 2023Topic-Selective Graph Network for Topic-Focused Summarizationcited by 4
  2. 2023P^3SUM: Preserving Author's Perspective in News Summarization with Diffusion Language Modelscited by 4
  3. 2023Neural Summarization of Electronic Health Recordscited by 3
  4. 2022Attend to the Right Context: A Plug-and-Play Module for Content-Controllable Summarizationcited by 2
  5. 2024Label-Free Topic-Focused Summarization Using Query Augmentationcited by 2
  6. 2025Beyond Multiple Choice: Evaluating Steering Vectors for Summarizationcited by 2
  7. 2025Adaptive Planning for Multi-Attribute Controllable Summarization with Monte Carlo Tree Searchcited by 2
  8. 2023Controllable Topic-Focused Abstractive Summarizationcited by 1
  9. 2024Exploring Iterative Controllable Summarization with Large Language Modelscited by 1
  10. 2026MATCHA: Matching Text via Contrastive Semantic Alignmentcited by 1
  11. 2022Topic-Controllable Summarization: Topic-Aware Evaluation and Transformer Methodscited by 0
  12. 2024MARS: Multilingual Aspect-centric Review Summarisationcited by 0
  13. 2025Logit Reweighting for Topic-Focused Summarizationcited by 0
  14. 2026LLMs Should Incorporate Explicit Mechanisms for Human Empathycited by 0
  15. 2026Query-Focused Event Summarization: A Dataset and Benchmarkcited by 0