12 citations · 21 across the 5 of their papers we have counts for
5 papers
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…
Challenges and Strategies in Cross-Cultural NLP
Daniel Hershcovich, Stella Frank, Heather Lent +11
Various efforts in the Natural Language Processing (NLP) community have been made to accommodate linguistic diversity and serve speakers of many different languages. However, it is…
Improved Multi-label Classification under Temporal Concept Drift: Rethinking Group-Robust Algorithms in a Label-Wise Setting
Ilias Chalkidis, Anders Søgaard
In document classification for, e.g., legal and biomedical text, we often deal with hundreds of classes, including very infrequent ones, as well as temporal concept drift caused by…
FairLex: A Multilingual Benchmark for Evaluating Fairness in Legal Text Processing
Ilias Chalkidis, Tommaso Pasini, Sheng Zhang +3
We present a benchmark suite of four datasets for evaluating the fairness of pre-trained language models and the techniques used to fine-tune them for downstream tasks. Our benchma…
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…