activity
20162026
most citedExtreme Multi-Label Legal Text Classification: A case study in EU Legislation

22 citations · 108 across the 66 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

cs.CL2020

Complaint Identification in Social Media with Transformer Networks

Mali Jin, Nikolaos Aletras

Complaining is a speech act extensively used by humans to communicate a negative inconsistency between reality and expectations. Previous work on automatically identifying complain…

cs.CL2020

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…

cs.CL2020

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…

cs.CL2020★ 2 cited

Point-of-Interest Type Inference from Social Media Text

Danae Sánchez Villegas, Daniel Preoţiuc-Pietro, Nikolaos Aletras

Physical places help shape how we perceive the experiences we have there. For the first time, we study the relationship between social media text and the type of the place from whe…

cs.IR2020★ 8 cited

Automatic Generation of Topic Labels

Areej Alokaili, Nikolaos Aletras, Mark Stevenson

Topic modelling is a popular unsupervised method for identifying the underlying themes in document collections that has many applications in information retrieval. A topic is usual…

cs.CL2020

Unsupervised Quality Estimation for Neural Machine Translation

Marina Fomicheva, Shuo Sun, Lisa Yankovskaya +6

Quality Estimation (QE) is an important component in making Machine Translation (MT) useful in real-world applications, as it is aimed to inform the user on the quality of the MT o…