activity
20192026
most citedLEXTREME: A Multi-Lingual and Multi-Task Benchmark for the Legal Domain

48 citations · 121 across the 23 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CL2024★ 4 cited

INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge

Angelika Romanou, Negar Foroutan, Anna Sotnikova +56

The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…

cs.CL2024★ 1 cited

From Citations to Criticality: Predicting Legal Decision Influence in the Multilingual Swiss Jurisprudence

Ronja Stern, Ken Kawamura, Matthias Stürmer +2

Many court systems are overwhelmed all over the world, leading to huge backlogs of pending cases. Effective triage systems, like those in emergency rooms, could ensure proper prior…

cs.CL2024★ 1 cited

Unlocking Legal Knowledge: A Multilingual Dataset for Judicial Summarization in Switzerland

Luca Rolshoven, Vishvaksenan Rasiah, Srinanda Brügger Bose +4

Legal research depends on headnotes: concise summaries that help lawyers quickly identify relevant cases. Yet, many court decisions lack them due to the high cost of manual annotat…

cs.CL2024

LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain

Joel Niklaus, Lucia Zheng, Arya D. McCarthy +7

Instruction tuning is an important step in making language models useful for direct user interaction. However, the legal domain is underrepresented in typical instruction datasets…

cs.CL2024★ 1 cited

Towards Explainability and Fairness in Swiss Judgement Prediction: Benchmarking on a Multilingual Dataset

Santosh T. Y. S. S, Nina Baumgartner, Matthias Stürmer +2

The assessment of explainability in Legal Judgement Prediction (LJP) systems is of paramount importance in building trustworthy and transparent systems, particularly considering th…

cs.CL2024★ 3 cited

LegalLens: Leveraging LLMs for Legal Violation Identification in Unstructured Text

Dor Bernsohn, Gil Semo, Yaron Vazana +5

In this study, we focus on two main tasks, the first for detecting legal violations within unstructured textual data, and the second for associating these violations with potential…