Papers with SJP
An Empirical Study on Cross-X Transfer for Legal Judgment Prediction (2022.aacl-main)
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| Challenge: | Cross-lingual transfer learning is understudied in legal NLP but not in legal Judgment Prediction (LJP). |
| Approach: | They explore cross-lingual transfer learning techniques on legal JP using a trilingual Swiss-Judgment-Prediction dataset and adapter-based fine-tuning. |
| Outcome: | The proposed methods improve the model’s performance by augmenting the training dataset with machine-translated versions of the original documents, using a 3 larger training corpus. |
Towards Explainability and Fairness in Swiss Judgement Prediction: Benchmarking on a Multilingual Dataset (2024.lrec-main)
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| Challenge: | Using Swiss Judgement Prediction, we evaluate the explainability of state-of-the-art monolingual and multilingual LJP models. |
| Approach: | They propose an occlusion-based approach to evaluate the explainability performance of legal judgement prediction models using Swiss Judgement Prediction, the only available multilingual LJP dataset. |
| Outcome: | The proposed framework allows us to quantify the influence of lower court information on model predictions, exposing current models’ biases. |