599 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National and Kapodistrian University of AthensGR24 papers
- National Technical University of AthensGR11 papers
- Athena Research and Innovation Center In Information Communication & Knowledge TechnologiesGR9 papers
- Athens State UniversityUS7 papers
- Centre National de la Recherche ScientifiqueFR7 papers
- Centrum Wiskunde & InformaticaNL7 papers
- Delft University of TechnologyNL7 papers
- École PolytechniqueFR7 papers
- University College LondonGB7 papers
- University of OxfordGB7 papers
- Laboratoire d'Informatique de l'École PolytechniqueFR6 papers
- University of AmsterdamNL6 papers
24 papers · 1 filter
Dialect Normalization using Large Language Models and Morphological Rules
Antonios Dimakis, John Pavlopoulos, Antonios Anastasopoulos
Natural language understanding systems struggle with low-resource languages, including many dialects of high-resource ones. Dialect-to-standard normalization attempts to tackle thi…
Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey
Katerina Korre, Dimitris Tsirmpas, Nikos Gkoumas +5
We present a survey of methods for assessing and enhancing the quality of online discussions, focusing on the potential of LLMs. While online discourses aim, at least in theory, to…
Local Explanations and Self-Explanations for Assessing Faithfulness in black-box LLMs
Christos Fragkathoulas, Odysseas S. Chlapanis
This paper introduces a novel task to assess the faithfulness of large language models (LLMs) using local perturbations and self-explanations. Many LLMs often require additional co…
Evaluating the Reliability of Self-Explanations in Large Language Models
Korbinian Randl, John Pavlopoulos, Aron Henriksson +1
This paper investigates the reliability of explanations generated by large language models (LLMs) when prompted to explain their previous output. We evaluate two kinds of such self…
Making LLMs Worth Every Penny: Resource-Limited Text Classification in Banking
Lefteris Loukas, Ilias Stogiannidis, Odysseas Diamantopoulos +2
Standard Full-Data classifiers in NLP demand thousands of labeled examples, which is impractical in data-limited domains. Few-shot methods offer an alternative, utilizing contrasti…
Neural Natural Language Processing for Long Texts: A Survey on Classification and Summarization
Dimitrios Tsirmpas, Ioannis Gkionis, Georgios Th. Papadopoulos +1
The adoption of Deep Neural Networks (DNNs) has greatly benefited Natural Language Processing (NLP) during the past decade. However, the demands of long document analysis are quite…
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…
Toxicity Detection can be Sensitive to the Conversational Context
Alexandros Xenos, John Pavlopoulos, Ion Androutsopoulos +3
User posts whose perceived toxicity depends on the conversational context are rare in current toxicity detection datasets. Hence, toxicity detectors trained on existing datasets wi…
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…
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…
How COVID-19 Is Changing Our Language : Detecting Semantic Shift in Twitter Word Embeddings
Yanzhu Guo, Christos Xypolopoulos, Michalis Vazirgiannis
Words are malleable objects, influenced by events that are reflected in written texts. Situated in the global outbreak of COVID-19, our research aims at detecting semantic shifts i…
GREEK-BERT: The Greeks visiting Sesame Street
John Koutsikakis, Ilias Chalkidis, Prodromos Malakasiotis +1
Transformer-based language models, such as BERT and its variants, have achieved state-of-the-art performance in several downstream natural language processing (NLP) tasks on generi…
Speaker-change Aware CRF for Dialogue Act Classification
Guokan Shang, Antoine Jean-Pierre Tixier, Michalis Vazirgiannis +1
Recent work in Dialogue Act (DA) classification approaches the task as a sequence labeling problem, using neural network models coupled with a Conditional Random Field (CRF) as the…
SumQE: a BERT-based Summary Quality Estimation Model
Stratos Xenouleas, Prodromos Malakasiotis, Marianna Apidianaki +1
We propose SumQE, a novel Quality Estimation model for summarization based on BERT. The model addresses linguistic quality aspects that are only indirectly captured by content-base…
Attention-based method for categorizing different types of online harassment language
Christos Karatsalos, Yannis Panagiotakis
In the era of social media and networking platforms, Twitter has been doomed for abuse and harassment toward users specifically women. Monitoring the contents including sexism and…
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…
Energy-based Self-attentive Learning of Abstractive Communities for Spoken Language Understanding
Guokan Shang, Antoine Jean-Pierre Tixier, Michalis Vazirgiannis +1
Abstractive community detection is an important spoken language understanding task, whose goal is to group utterances in a conversation according to whether they can be jointly sum…
Evaluation of Greek Word Embeddings
Stamatis Outsios, Christos Karatsalos, Konstantinos Skianis +1
Since word embeddings have been the most popular input for many NLP tasks, evaluating their quality is of critical importance. Most research efforts are focusing on English word em…
SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression
Christos Baziotis, Ion Androutsopoulos, Ioannis Konstas +1
Neural sequence-to-sequence models are currently the dominant approach in several natural language processing tasks, but require large parallel corpora. We present a sequence-to-se…
Extracting Linguistic Resources from the Web for Concept-to-Text Generation
Gerasimos Lampouras, Ion Androutsopoulos
Many concept-to-text generation systems require domain-specific linguistic resources to produce high quality texts, but manually constructing these resources can be tedious and cos…
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization
Guokan Shang, Wensi Ding, Zekun Zhang +4
We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations. Our work combines the stren…
Generating Natural Language Descriptions from OWL Ontologies: the NaturalOWL System
Ion Androutsopoulos, Gerasimos Lampouras, Dimitrios Galanis
We present NaturalOWL, a natural language generation system that produces texts describing individuals or classes of OWL ontologies. Unlike simpler OWL verbalizers, which typically…
Text Relatedness Based on a Word Thesaurus
George Tsatsaronis, Iraklis Varlamis, Michalis Vazirgiannis
The computation of relatedness between two fragments of text in an automated manner requires taking into account a wide range of factors pertaining to the meaning the two fragments…
A Survey of Paraphrasing and Textual Entailment Methods
Ion Androutsopoulos, Prodromos Malakasiotis
Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural language expressions that convey almost the same information. Textual entailment methods,…