activity
20192022
most citedAn Empirical Study on Cross-X Transfer for Legal Judgment Prediction

7 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20223 cited

BudgetLongformer: Can we Cheaply Pretrain a SotA Legal Language Model From Scratch?

Joel Niklaus, Daniele Giofré

Pretrained transformer models have achieved state-of-the-art results in many tasks and benchmarks recently. Many state-of-the-art Language Models (LMs), however, do not scale well…

cs.CL2022

ClassActionPrediction: A Challenging Benchmark for Legal Judgment Prediction of Class Action Cases in the US

Gil Semo, Dor Bernsohn, Ben Hagag +2

The research field of Legal Natural Language Processing (NLP) has been very active recently, with Legal Judgment Prediction (LJP) becoming one of the most extensively studied tasks…

cs.CL20227 cited

An Empirical Study on Cross-X Transfer for Legal Judgment Prediction

Joel Niklaus, Matthias Stürmer, Ilias Chalkidis

Cross-lingual transfer learning has proven useful in a variety of Natural Language Processing (NLP) tasks, but it is understudied in the context of legal NLP, and not at all in Leg…

cs.CL20211 cited

Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark

Joel Niklaus, Ilias Chalkidis, Matthias Stürmer

In many jurisdictions, the excessive workload of courts leads to high delays. Suitable predictive AI models can assist legal professionals in their work, and thus enhance and speed…

cs.AI2019

Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game Jass

Joel Niklaus, Michele Alberti, Vinaychandran Pondenkandath +2

In the last decades we have witnessed the success of applications of Artificial Intelligence to playing games. In this work we address the challenging field of games with hidden in…