mlsanityData to 14 Oct 2026

Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature

arXiv 2210.09932 ↗First posted 18 Oct 2022cs.CLcited by 55

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Abstract (arXiv)

Lay summarisation aims to jointly summarise and simplify a given text, thus making its content more comprehensible to non-experts. Automatic approaches for lay summarisation can provide significant value in broadening access to scientific literature, enabling a greater degree of both interdisciplinary knowledge sharing and public understanding when it comes to research findings. However, current corpora for this task are limited in their size and scope, hindering the development of broadly applicable data-driven approaches. Aiming to rectify these issues, we present two novel lay summarisation datasets, PLOS (large-scale) and eLife (medium-scale), each of which contains biomedical journal articles alongside expert-written lay summaries. We provide a thorough characterisation of our lay summaries, highlighting differing levels of readability and abstractiveness between datasets that can be leveraged to support the needs of different applications. Finally, we benchmark our datasets using mainstream summarisation approaches and perform a manual evaluation with domain experts, demonstrating their utility and casting light on the key challenges of this task.

Key facts. Cited by 55 papers in the map (data through 14 Oct 2026). Builds on 16 of its 32 references that are in the map. First posted on arXiv 18 Oct 2022.

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16 of 32 references.

References · 16

  1. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  2. 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,218
  3. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,414
  4. 2017Get To The Point: Summarization with Pointer-Generator Networkscited by 1,292
  5. 2020On Faithfulness and Factuality in Abstractive Summarizationcited by 900
  6. 2018A Discourse-Aware Attention Model for Abstractive Summarization of Long Documentscited by 478
  7. 2016SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documentscited by 246
  8. 2019ScispaCy: Fast and Robust Models for Biomedical Natural Language Processingcited by 244
  9. 2019BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarizationcited by 156
  10. 2020TLDR: Extreme Summarization of Scientific Documentscited by 136
  11. 2017PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstractscited by 124
  12. 2019Pretrained Language Models for Sequential Sentence Classificationcited by 53
4 more
  1. 2021Paragraph-level Simplification of Medical Textscited by 53
  2. 2019EASSE: Easier Automatic Sentence Simplification Evaluationcited by 50
  3. 2020Automated Lay Language Summarization of Biomedical Scientific Reviewscited by 46
  4. 2020PySBD: Pragmatic Sentence Boundary Disambiguationcited by 38

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 18; 2024: 16; 2025: 11; 2026: 9.

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  1. 2023MeetingBank: A Benchmark Dataset for Meeting Summarizationcited by 84
  2. 2023FactKB: Generalizable Factuality Evaluation using Language Models Enhanced with Factual Knowledgecited by 55
  3. 2023ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfercited by 50
  4. 2025Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluationcited by 42
  5. 2024SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literaturecited by 41
  6. 2023A Comprehensive Evaluation of Large Language Models on Benchmark Biomedical Text Processing Taskscited by 36
  7. 2023Generating Summaries with Controllable Readability Levelscited by 24
  8. 2025Paper2Video: Automatic Video Generation from Scientific Paperscited by 24
  9. 2024RAG-RLRC-LaySum at BioLaySumm: Integrating Retrieval-Augmented Generation and Readability Control for Layman Summarization of Biomedical Textscited by 23
  10. 2022Retrieval augmentation of large language models for lay language generationcited by 21
  11. 2024Overview of the BioLaySumm 2024 Shared Task on the Lay Summarization of Biomedical Research Articlescited by 18
  12. 2023Incorporating Distributions of Discourse Structure for Long Document Abstractive Summarizationcited by 17
38 more
  1. 2023README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLPcited by 17
  2. 2024A Comprehensive Survey on Evaluating Large Language Model Applications in the Medical Industrycited by 17
  3. 2023DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLMcited by 16
  4. 2024SciNews: From Scholarly Complexities to Public Narratives -- A Dataset for Scientific News Report Generationcited by 12
  5. 2023The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generationcited by 11
  6. 2024RST-LoRA: A Discourse-Aware Low-Rank Adaptation for Long Document Abstractive Summarizationcited by 11
  7. 2024RSA-Control: A Pragmatics-Grounded Lightweight Controllable Text Generation Frameworkcited by 11
  8. 2024ReadCtrl: Personalizing text generation with readability-controlled instruction learningcited by 10
  9. 2023Improving Biomedical Abstractive Summarisation with Knowledge Aggregation from Citation Paperscited by 9
  10. 2023Enhancing Biomedical Lay Summarisation with External Knowledge Graphscited by 8
  11. 2023Overview of the BioLaySumm 2023 Shared Task on Lay Summarization of Biomedical Research Articlescited by 6
  12. 2024Can Large Language Model Summarizers Adapt to Diverse Scientific Communication Goals?cited by 6
  13. 2025Evaluating the Evaluators: Are readability metrics good measures of readability?cited by 6
  14. 2025Magical: Medical Lay Language Generation via Semantic Invariance and Layperson-tailored Adaptationcited by 5
  15. 2023Automatic and Human-AI Interactive Text Generationcited by 4
  16. 2023P^3SUM: Preserving Author's Perspective in News Summarization with Diffusion Language Modelscited by 4
  17. 2025Compressing Language Models for Specialized Domainscited by 4
  18. 2025Explanatory Summarization with Discourse-Driven Planningcited by 4
  19. 2023Ascle: A Python Natural Language Processing Toolkit for Medical Text Generationcited by 3
  20. 2024Science Out of Its Ivory Tower: Improving Accessibility with Reinforcement Learningcited by 3
  21. 2025JRE-L: Journalist, Reader, and Editor LLMs in the Loop for Science Journalism for the General Audiencecited by 3
  22. 2025Sci-LoRA: Mixture of Scientific LoRAs for Cross-Domain Lay Paraphrasingcited by 3
  23. 2024ATLAS: Improving Lay Summarisation with Attribute-based Controlcited by 2
  24. 2024LLM-Collaboration on Automatic Science Journalism for the General Audiencecited by 2
  25. 2024A Critical Look at Meta-evaluating Summarisation Evaluation Metricscited by 2
  26. 2023Language Model as an Annotator: Unsupervised Context-aware Quality Phrase Generationcited by 1
  27. 2024WisPerMed at BioLaySumm: Adapting Autoregressive Large Language Models for Lay Summarization of Scientific Articlescited by 1
  28. 2024Simplifying Scholarly Abstracts for Accessible Digital Librariescited by 1
  29. 2025FActBench: A Benchmark for Fine-grained Automatic Evaluation of LLM-Generated Text in the Medical Domaincited by 1
  30. 2025PERCS: Persona-Guided Controllable Biomedical Summarization Datasetcited by 1
  31. 2026MedLayBench-V: A Large-Scale Benchmark for Expert-Lay Semantic Alignment in Medical Vision Language Modelscited by 1
  32. 2023SimCSum: Joint Learning of Simplification and Cross-lingual Summarization for Cross-lingual Science Journalismcited by 0
  33. 2023Background Knowledge Grounding for Readable, Relevant, and Factual Biomedical Lay Summariescited by 0
  34. 2024The Lay Person's Guide to Biomedicine: Orchestrating Large Language Modelscited by 0
  35. 2025Not too long do read: Evaluating LLM-generated extreme scientific summariescited by 0
  36. 2026From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoningcited by 0
  37. 2026No Reader Left Behind: Multi-Agent Summaries Everyone Can Understandcited by 0
  38. 2026MEDLAYXPLAIN: Benchmarking the Expert-Lay Gap in Medical Vision-Language Modelscited by 0

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