338 citations · 698 across the 54 of their papers we have counts for
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Truthful Meta-Explanations for Local Interpretability of Machine Learning Models
Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas
Automated Machine Learning-based systems' integration into a wide range of tasks has expanded as a result of their performance and speed. Although there are numerous advantages to…
Fine-Grained Selective Similarity Integration for Drug-Target Interaction Prediction
Bin Liu, Jin Wang, Kaiwei Sun +1
The discovery of drug-target interactions (DTIs) is a pivotal process in pharmaceutical development. Computational approaches are a promising and efficient alternative to tedious a…
Artificial Disfluency Detection, Uh No, Disfluency Generation for the Masses
T. Passali, T. Mavropoulos, G. Tsoumakas +2
Existing approaches for disfluency detection typically require the existence of large annotated datasets. However, current datasets for this task are limited, suffer from class imb…
An Attention Matrix for Every Decision: Faithfulness-based Arbitration Among Multiple Attention-Based Interpretations of Transformers in Text Classification
Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas
Transformers are widely used in natural language processing, where they consistently achieve state-of-the-art performance. This is mainly due to their attention-based architecture,…
Local Multi-Label Explanations for Random Forest
Nikolaos Mylonas, Ioannis Mollas, Nick Bassiliades +1
Multi-label classification is a challenging task, particularly in domains where the number of labels to be predicted is large. Deep neural networks are often effective at multi-lab…
Topic-Controllable Summarization: Topic-Aware Evaluation and Transformer Methods
Tatiana Passali, Grigorios Tsoumakas
Topic-controllable summarization is an emerging research area with a wide range of potential applications. However, existing approaches suffer from significant limitations. For exa…
Local Explanation of Dimensionality Reduction
Avraam Bardos, Ioannis Mollas, Nick Bassiliades +1
Dimensionality reduction (DR) is a popular method for preparing and analyzing high-dimensional data. Reduced data representations are less computationally intensive and easier to m…
Multiple Similarity Drug-Target Interaction Prediction with Random Walks and Matrix Factorization
Bin Liu, Dimitrios Papadopoulos, Fragkiskos D. Malliaros +2
The discovery of drug-target interactions (DTIs) is a very promising area of research with great potential. The accurate identification of reliable interactions among drugs and pro…
LARD: Large-scale Artificial Disfluency Generation
T. Passali, T. Mavropoulos, G. Tsoumakas +2
Disfluency detection is a critical task in real-time dialogue systems. However, despite its importance, it remains a relatively unexplored field, mainly due to the lack of appropri…