mlsanityData to 7 Oct 2026

Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation

arXiv 2210.07544 ↗First posted 14 Oct 2022cs.CL cs.IRcited by 23

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Abstract (arXiv)

Summarization of legal case judgement documents is a challenging problem in Legal NLP. However, not much analyses exist on how different families of summarization models (e.g., extractive vs. abstractive) perform when applied to legal case documents. This question is particularly important since many recent transformer-based abstractive summarization models have restrictions on the number of input tokens, and legal documents are known to be very long. Also, it is an open question on how best to evaluate legal case document summarization systems. In this paper, we carry out extensive experiments with several extractive and abstractive summarization methods (both supervised and unsupervised) over three legal summarization datasets that we have developed. Our analyses, that includes evaluation by law practitioners, lead to several interesting insights on legal summarization in specific and long document summarization in general.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 22 of its 39 references that are in the map. First posted on arXiv 14 Oct 2022.

Builds on

22 of 39 references.

References · 22

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10 more
  1. 2019BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarizationcited by 155
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Citing papers per year: 2022: 2; 2023: 4; 2024: 7; 2025: 6; 2026: 4.

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  1. 2022ECTSum: A New Benchmark Dataset For Bullet Point Summarization of Long Earnings Call Transcriptscited by 59
  2. 2023How Ready are Pre-trained Abstractive Models and LLMs for Legal Case Judgement Summarization?cited by 43
  3. 2023Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Modelscited by 35
  4. 2022Named Entity Recognition in Indian court judgmentscited by 26
  5. 2024Applicability of Large Language Models and Generative Models for Legal Case Judgement Summarizationcited by 23
  6. 2024Low-Resource Court Judgment Summarization for Common Law Systemscited by 11
  7. 2023MILDSum: A Novel Benchmark Dataset for Multilingual Summarization of Indian Legal Case Judgmentscited by 10
  8. 2025A Comprehensive Survey on Legal Summarization: Challenges and Future Directionscited by 6
  9. 2025Magical: Medical Lay Language Generation via Semantic Invariance and Layperson-tailored Adaptationcited by 5
  10. 2024CTISum: A New Benchmark Dataset For Cyber Threat Intelligence Summarizationcited by 2
  11. 2024Quebec Automobile Insurance Question-Answering With Retrieval-Augmented Generationcited by 2
  12. 2024How Private are Language Models in Abstractive Summarization?cited by 2
11 more
  1. 2023Automated Argument Generation from Legal Factscited by 1
  2. 2024Human Centered AI for Indian Legal Text Analyticscited by 1
  3. 2024Unveiling Themes in Judicial Proceedings: A Cross-Country Study Using Topic Modeling on Legal Documents from India and the UKcited by 1
  4. 2026Evaluation of Large Language Models in Legal Applications: Challenges, Methods, and Future Directionscited by 1
  5. 2025Nyay-Darpan: Enhancing Decision Making Through Summarization and Case Retrieval for Consumer Law in Indiacited by 0
  6. 2025LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documentscited by 0
  7. 2025AugAbEx: Bridging Abstractive and Extractive Legal Summarizationcited by 0
  8. 2025CourtPressGER: A German Court Decision to Press Release Summarization Datasetcited by 0
  9. 2026Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizerscited by 0
  10. 2026Annotating Topical Legal Insights from Case Proceedingscited by 0
  11. 2026Rent-a-RAG: Embedding-Space Watermarks for Auditing Third-Party RAGcited by 0