4 citations · 7 across the 11 of their papers we have counts for
11 papers
LP-Eval: Rubric and Dataset for Measuring the Quality of Legal Proposition Generation
Shanshan Xu, Johan Lindholm, Amogh Raina +2
Legal proposition generation is central to legal reasoning and doctrinal scholarship, yet remain under-examined in Legal NLP. This paper investigates the automatic generation and e…
From Knowledge to Inference: Formalizing Specialized Public Health Reasoning on GlobalHealthAtlas
Zhaokun Yan, Shan Xu, Wuzheng Dong +10
Public health reasoning requires population level inference grounded in scientific evidence, expert consensus, and safety constraints. However, it remains underexplored as a struct…
Efficient Prompt Optimisation for Legal Text Classification with Proxy Prompt Evaluator
Hyunji Lee, Kevin Chenhao Li, Matthias Grabmair +1
Prompt optimization aims to systematically refine prompts to enhance a language model's performance on specific tasks. Fairness detection in Terms of Service (ToS) clauses is a cha…
Better Aligned with Survey Respondents or Training Data? Unveiling Political Leanings of LLMs on U.S. Supreme Court Cases
Shanshan Xu, T. Y. S. S Santosh, Yanai Elazar +3
Recent works have shown that Large Language Models (LLMs) have a tendency to memorize patterns and biases present in their training data, raising important questions about how such…
The Craft of Selective Prediction: Towards Reliable Case Outcome Classification -- An Empirical Study on European Court of Human Rights Cases
T. Y. S. S. Santosh, Irtiza Chowdhury, Shanshan Xu +1
In high-stakes decision-making tasks within legal NLP, such as Case Outcome Classification (COC), quantifying a model's predictive confidence is crucial. Confidence estimation enab…
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…
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…
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…
Attack on Unfair ToS Clause Detection: A Case Study using Universal Adversarial Triggers
Shanshan Xu, Irina Broda, Rashid Haddad +2
Recent work has demonstrated that natural language processing techniques can support consumer protection by automatically detecting unfair clauses in the Terms of Service (ToS) Agr…
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…
Extractive Summarization of Legal Decisions using Multi-task Learning and Maximal Marginal Relevance
Abhishek Agarwal, Shanshan Xu, Matthias Grabmair
Summarizing legal decisions requires the expertise of law practitioners, which is both time- and cost-intensive. This paper presents techniques for extractive summarization of lega…