52 citations · 131 across the 10 of their papers we have counts for
12 papers
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…
FiNER: Financial Numeric Entity Recognition for XBRL Tagging
Lefteris Loukas, Manos Fergadiotis, Ilias Chalkidis +4
Publicly traded companies are required to submit periodic reports with eXtensive Business Reporting Language (XBRL) word-level tags. Manually tagging the reports is tedious and cos…
EDGAR-CORPUS: Billions of Tokens Make The World Go Round
Lefteris Loukas, Manos Fergadiotis, Ion Androutsopoulos +1
We release EDGAR-CORPUS, a novel corpus comprising annual reports from all the publicly traded companies in the US spanning a period of more than 25 years. To the best of our knowl…
DICoE@FinSim-3: Financial Hypernym Detection using Augmented Terms and Distance-based Features
Lefteris Loukas, Konstantinos Bougiatiotis, Manos Fergadiotis +2
We present the submission of team DICoE for FinSim-3, the 3rd Shared Task on Learning Semantic Similarities for the Financial Domain. The task provides a set of terms in the financ…
MultiEURLEX -- A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer
Ilias Chalkidis, Manos Fergadiotis, Ion Androutsopoulos
We introduce MULTI-EURLEX, a new multilingual dataset for topic classification of legal documents. The dataset comprises 65k European Union (EU) laws, officially translated in 23 l…
Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases
Ilias Chalkidis, Manos Fergadiotis, Dimitrios Tsarapatsanis +3
Interpretability or explainability is an emerging research field in NLP. From a user-centric point of view, the goal is to build models that provide proper justification for their…
Neural Contract Element Extraction Revisited: Letters from Sesame Street
Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis +1
We investigate contract element extraction. We show that LSTM-based encoders perform better than dilated CNNs, Transformers, and BERT in this task. We also find that domain-specifi…
Regulatory Compliance through Doc2Doc Information Retrieval: A case study in EU/UK legislation where text similarity has limitations
Ilias Chalkidis, Manos Fergadiotis, Nikolaos Manginas +2
Major scandals in corporate history have urged the need for regulatory compliance, where organizations need to ensure that their controls (processes) comply with relevant laws, reg…
LEGAL-BERT: The Muppets straight out of Law School
Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis +2
BERT has achieved impressive performance in several NLP tasks. However, there has been limited investigation on its adaptation guidelines in specialised domains. Here we focus on t…
An Empirical Study on Large-Scale Multi-Label Text Classification Including Few and Zero-Shot Labels
Ilias Chalkidis, Manos Fergadiotis, Sotiris Kotitsas +3
Large-scale Multi-label Text Classification (LMTC) has a wide range of Natural Language Processing (NLP) applications and presents interesting challenges. First, not all labels are…
Large-Scale Multi-Label Text Classification on EU Legislation
Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis +1
We consider Large-Scale Multi-Label Text Classification (LMTC) in the legal domain. We release a new dataset of 57k legislative documents from EURLEX, annotated with ~4.3k EUROVOC…
Extreme Multi-Label Legal Text Classification: A case study in EU Legislation
Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis +2
We consider the task of Extreme Multi-Label Text Classification (XMTC) in the legal domain. We release a new dataset of 57k legislative documents from EURLEX, the European Union's…