Summary of Unlocking Legal Knowledge: a Multilingual Dataset For Judicial Summarization in Switzerland, by Luca Rolshoven et al.
Unlocking Legal Knowledge: A Multilingual Dataset for Judicial Summarization in Switzerland
by Luca Rolshoven, Vishvaksenan Rasiah, Srinanda Brügger Bose, Matthias Stürmer, Joel Niklaus
First submitted to arxiv on: 17 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces the Swiss Leading Decision Summarization (SLDS) dataset, a novel cross-lingual resource featuring 18K court rulings from the Swiss Federal Supreme Court (SFSC), in German, French, and Italian, along with German headnotes. The goal is to facilitate automated headnote creation for legal research, making hundreds of thousands of decisions more accessible in Switzerland alone. Three mT5 variants are fine-tuned and evaluated alongside proprietary models. Results show that while proprietary models perform well in zero-shot and one-shot settings, fine-tuned smaller models still provide a strong competitive edge. The dataset is publicly released to promote further research in multilingual legal summarization and the development of assistive technologies for legal professionals. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper helps make it easier for lawyers to find important cases by creating a special kind of summary called an “headnote”. Currently, writing these headnotes takes a lot of time. The researchers created a big dataset with many court rulings from Switzerland, along with summaries in three languages. They tested different models to see which ones work best at making summaries. Their results show that using smaller models and fine-tuning them can be just as good as using more powerful models. The dataset is now available for others to use and improve upon. |
Keywords
» Artificial intelligence » Fine tuning » One shot » Summarization » Zero shot
