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20222025
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cs.CL2025

CoCoLex: Confidence-guided Copy-based Decoding for Grounded Legal Text Generation

Santosh T. Y. S. S, Youssef Tarek Elkhayat, Oana Ichim +5

Due to their ability to process long and complex contexts, LLMs can offer key benefits to the Legal domain, but their adoption has been hindered by their tendency to generate unfai…

cs.CL2025

LexGenie: Automated Generation of Structured Reports for European Court of Human Rights Case Law

T. Y. S. S Santosh, Mahmoud Aly, Oana Ichim +1

Analyzing large volumes of case law to uncover evolving legal principles, across multiple cases, on a given topic is a demanding task for legal professionals. Structured topical re…

cs.CL2024

Through the Lens of Split Vote: Exploring Disagreement, Difficulty and Calibration in Legal Case Outcome Classification

Shanshan Xu, T. Y. S. S Santosh, Oana Ichim +2

In legal decisions, split votes (SV) occur when judges cannot reach a unanimous decision, posing a difficulty for lawyers who must navigate diverse legal arguments and opinions. In…

cs.CL2023

VECHR: A Dataset for Explainable and Robust Classification of Vulnerability Type in the European Court of Human Rights

Shanshan Xu, Leon Staufer, T. Y. S. S Santosh +3

Recognizing vulnerability is crucial for understanding and implementing targeted support to empower individuals in need. This is especially important at the European Court of Human…

cs.CL2023

From Dissonance to Insights: Dissecting Disagreements in Rationale Construction for Case Outcome Classification

Shanshan Xu, T. Y. S. S Santosh, Oana Ichim +3

In legal NLP, Case Outcome Classification (COC) must not only be accurate but also trustworthy and explainable. Existing work in explainable COC has been limited to annotations by…

cs.CL2022

Deconfounding Legal Judgment Prediction for European Court of Human Rights Cases Towards Better Alignment with Experts

T. Y. S. S Santosh, Shanshan Xu, Oana Ichim +1

This work demonstrates that Legal Judgement Prediction systems without expert-informed adjustments can be vulnerable to shallow, distracting surface signals that arise from corpus…