Summary of Improving Legal Judgement Prediction in Romanian with Long Text Encoders, by Mihai Masala et al.
Improving Legal Judgement Prediction in Romanian with Long Text Encoders
by Mihai Masala, Traian Rebedea, Horia Velicu
First submitted to arxiv on: 29 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 investigates the prediction of final rulings in legal cases using Natural Language Processing (NLP) techniques. The authors focus on developing specialized models and methods for the Legal Judgment Prediction (LJP) task, which requires understanding long documents specific to the legal domain. They experiment with 4 LJP datasets in Romanian, showing that handling long texts and using specialized models are crucial for good performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The researchers explore ways to improve the accuracy of predicting legal judgments using NLP techniques. They develop customized models and methods specifically designed for this task, which involves analyzing long documents found in legal corpora. The team tests their approach on four datasets from Romania, highlighting the importance of adapting to the unique characteristics of legal text. |
Keywords
» Artificial intelligence » Natural language processing » Nlp
