17 citations · 21 across the 6 of their papers we have counts for
4 papers · 1 filter
Processing Long Legal Documents with Pre-trained Transformers: Modding LegalBERT and Longformer
Dimitris Mamakas, Petros Tsotsi, Ion Androutsopoulos +1
Pre-trained Transformers currently dominate most NLP tasks. They impose, however, limits on the maximum input length (512 sub-words in BERT), which are too restrictive in the legal…
An Exploration of Hierarchical Attention Transformers for Efficient Long Document Classification
Ilias Chalkidis, Xiang Dai, Manos Fergadiotis +2
Non-hierarchical sparse attention Transformer-based models, such as Longformer and Big Bird, are popular approaches to working with long documents. There are clear benefits to thes…
Realistic Zero-Shot Cross-Lingual Transfer in Legal Topic Classification
Stratos Xenouleas, Alexia Tsoukara, Giannis Panagiotakis +2
We consider zero-shot cross-lingual transfer in legal topic classification using the recent MultiEURLEX dataset. Since the original dataset contains parallel documents, which is un…
Revisiting Transformer-based Models for Long Document Classification
Xiang Dai, Ilias Chalkidis, Sune Darkner +1
The recent literature in text classification is biased towards short text sequences (e.g., sentences or paragraphs). In real-world applications, multi-page multi-paragraph document…