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Found 5 papers, 2 papers with code
Through the Lens of Split Vote: Exploring Disagreement, Difficulty and Calibration in Legal Case Outcome Classification
We observe limited alignment with the judge vote distribution.
From Dissonance to Insights: Dissecting Disagreements in Rationale Construction for Case Outcome Classification
Overall, our case study reveals hitherto underappreciated complexities in creating benchmark datasets in legal NLP that revolve around identifying aspects of a case's facts supposedly relevant to its outcome.
VECHR: A Dataset for Explainable and Robust Classification of Vulnerability Type in the European Court of Human Rights
Our results demonstrate the challenging nature of the task with lower prediction performance and limited agreement between models and experts.
Zero-shot Transfer of Article-aware Legal Outcome Classification for European Court of Human Rights Cases
In this paper, we cast Legal Judgment Prediction on European Court of Human Rights cases into an article-aware classification task, where the case outcome is classified from a combined input of case facts and convention articles.
Deconfounding Legal Judgment Prediction for European Court of Human Rights Cases Towards Better Alignment with Experts
This work demonstrates that Legal Judgement Prediction systems without expert-informed adjustments can be vulnerable to shallow, distracting surface signals that arise from corpus construction, case distribution, and confounding factors.
