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MS2: Multi-Document Summarization of Medical Studies

arXiv 2104.06486 ↗First posted 13 Apr 2021cs.CL cs.AI cs.LGcited by 80

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Abstract (arXiv)

To assess the effectiveness of any medical intervention, researchers must conduct a time-intensive and highly manual literature review. NLP systems can help to automate or assist in parts of this expensive process. In support of this goal, we release MS^2 (Multi-Document Summarization of Medical Studies), a dataset of over 470k documents and 20k summaries derived from the scientific literature. This dataset facilitates the development of systems that can assess and aggregate contradictory evidence across multiple studies, and is the first large-scale, publicly available multi-document summarization dataset in the biomedical domain. We experiment with a summarization system based on BART, with promising early results. We formulate our summarization inputs and targets in both free text and structured forms and modify a recently proposed metric to assess the quality of our system's generated summaries. Data and models are available at https://github.com/allenai/ms2

Key facts. Cited by 80 papers in the map (data through 7 Oct 2026). Builds on 37 of its 92 references that are in the map. First posted on arXiv 13 Apr 2021.

Builds on

37 of 92 references.

References · 37

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25 more
  1. 2019Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Modelcited by 431
  2. 2020SPECTER: Document-level Representation Learning using Citation-informed Transformerscited by 426
  3. 2020Asking and Answering Questions to Evaluate the Factual Consistency of Summariescited by 376
  4. 2018Generating Wikipedia by Summarizing Long Sequencescited by 333
  5. 2018Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Constructioncited by 321
  6. 2020CORD-19: The COVID-19 Open Research Datasetcited by 179
  7. 2018Lessons from Natural Language Inference in the Clinical Domaincited by 149
  8. 2020TLDR: Extreme Summarization of Scientific Documentscited by 136
  9. 2019Hierarchical Transformers for Multi-Document Summarizationcited by 132
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  11. 2020SciREX: A Challenge Dataset for Document-Level Information Extractioncited by 111
  12. 2020Pre-training via Paraphrasingcited by 92
  13. 2018A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literaturecited by 79
  14. 2020A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portalcited by 72
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  19. 2018Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document Summarizationcited by 42
  20. 2018Query Focused Abstractive Summarization: Incorporating Query Relevance, Multi-Document Coverage, and Summary Length Constraints into seq2seq Modelscited by 39
  21. 2020Evidence Inference 2.0: More Data, Better Modelscited by 39
  22. 2020Understanding Clinical Trial Reports: Extracting Medical Entities and Their Relationscited by 14
  23. 2019Overview and Results: CL-SciSumm Shared Task 2019cited by 7
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 16; 2023: 21; 2024: 12; 2025: 21; 2026: 5.

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  1. 2025Survey on Evaluation of LLM-based Agentscited by 190
  2. 2023A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethicscited by 162
  3. 2022Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Textcited by 154
  4. 2023LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarizationcited by 96
  5. 2022SciFact-Open: Towards open-domain scientific claim verificationcited by 94
  6. 2021Pre-trained Language Models in Biomedical Domain: A Systematic Surveycited by 87
  7. 2023Benchmarking large language models for biomedical natural language processing applications and recommendationscited by 78
  8. 2022An Empirical Survey on Long Document Summarization: Datasets, Models and Metricscited by 74
  9. 2022Generating Scientific Claims for Zero-Shot Scientific Fact Checkingcited by 59
  10. 2023Towards Interpretable Mental Health Analysis with Large Language Modelscited by 53
  11. 2022Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularitiescited by 47
  12. 2023Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articlescited by 45
38 more
  1. 2024SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literaturecited by 37
  2. 2024CHIME: LLM-Assisted Hierarchical Organization of Scientific Studies for Literature Review Supportcited by 28
  3. 2022NeuS: Neutral Multi-News Summarization for Mitigating Framing Biascited by 26
  4. 2025Multi-Agent-as-Judge: Aligning LLM-Agent-Based Automated Evaluation with Multi-Dimensional Human Evaluationcited by 26
  5. 2022ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Miningcited by 25
  6. 2025Paper2Video: Automatic Video Generation from Scientific Paperscited by 23
  7. 2021Literature-Augmented Clinical Outcome Predictioncited by 20
  8. 2022Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrievalcited by 20
  9. 2022Readability Controllable Biomedical Document Summarizationcited by 19
  10. 2023Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviewscited by 18
  11. 2023Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluationscited by 18
  12. 2023SciReviewGen: A Large-scale Dataset for Automatic Literature Review Generationcited by 17
  13. 2024From Single to Multi: How LLMs Hallucinate in Multi-Document Summarizationcited by 17
  14. 2025Multimodal Large Language Models for Medicine: A Comprehensive Surveycited by 16
  15. 2025When AIs Judge AIs: The Rise of Agent-as-a-Judge Evaluation for LLMscited by 16
  16. 2022A Survey on Medical Document Summarizationcited by 14
  17. 2024ETHIC: Evaluating Large Language Models on Long-Context Tasks with High Information Coveragecited by 12
  18. 2025Evolutionary Perspectives on the Evaluation of LLM-Based AI Agents: A Comprehensive Surveycited by 12
  19. 2023Do Multi-Document Summarization Models Synthesize?cited by 11
  20. 2025A foundation model for human-AI collaboration in medical literature miningcited by 11
  21. 2024Panacea: A foundation model for clinical trial search, summarization, design, and recruitmentcited by 10
  22. 2023Generating EDU Extracts for Plan-Guided Summary Re-Rankingcited by 9
  23. 2023Towards Argument-Aware Abstractive Summarization of Long Legal Opinions with Summary Rerankingcited by 9
  24. 2023Improving Biomedical Abstractive Summarisation with Knowledge Aggregation from Citation Paperscited by 9
  25. 2023FaMeSumm: Investigating and Improving Faithfulness of Medical Summarizationcited by 9
  26. 2021Semi-Supervised Exaggeration Detection of Health Science Press Releasescited by 8
  27. 2022How "Multi" is Multi-Document Summarization?cited by 8
  28. 2023What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarizationcited by 8
  29. 2024ArxivDIGESTables: Synthesizing Scientific Literature into Tables using Language Modelscited by 8
  30. 2023Automatically Summarizing Evidence from Clinical Trials: A Prototype Highlighting Current Challengescited by 7
  31. 2025SurveyGen: Quality-Aware Scientific Survey Generation with Large Language Modelscited by 7
  32. 2021SummerTime: Text Summarization Toolkit for Non-expertscited by 6
  33. 2024From Paper to Card: Transforming Design Implications with Generative AIcited by 6
  34. 2025arXiv2Table: Toward Realistic Benchmarking and Evaluation for LLM-Based Literature-Review Table Generationcited by 6
  35. 2022Community Question Answering Entity Linking via Leveraging Auxiliary Datacited by 5
  36. 2023CARE: Extracting Experimental Findings From Clinical Literaturecited by 5
  37. 2025RAG for Geoscience: What We Expect, Gaps and Opportunitiescited by 5
  38. 2025Benchmarking GPT-5 for biomedical natural language processingcited by 5

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