2 citations · 2 across the 7 of their papers we have counts for
7 papers
Optimal Recourse Summaries via Bi-Objective Decision Tree Learning
Ioannis Chatzis, Jason Liartis, Athanasios Voulodimos +1
Actionable Recourse provides individuals with actions they can take to change an unfavorable classifier outcome. While useful at the instance level, it is ill-suited for global aud…
Explain the Flag: Contextualizing Hate Speech Beyond Censorship
Jason Liartis, Eirini Kaldeli, Lambrini Gyftokosta +2
Hate, derogatory, and offensive speech remains a persistent challenge in online platforms and public discourse. While automated detection systems are widely used, most focus on cen…
Go witheFlow: Real-time Emotion Driven Audio Effects Modulation
Edmund Dervakos, Spyridon Kantarelis, Vassilis Lyberatos +2
Music performance is a distinctly human activity, intrinsically linked to the performer's ability to convey, evoke, or express emotion. Machines cannot perform music in the human s…
Don't Erase, Inform! Detecting and Contextualizing Harmful Language in Cultural Heritage Collections
Orfeas Menis Mastromichalakis, Jason Liartis, Kristina Rose +2
Cultural Heritage (CH) data hold invaluable knowledge, reflecting the history, traditions, and identities of societies, and shaping our understanding of the past and present. Howev…
Semantic Prototypes: Enhancing Transparency Without Black Boxes
Orfeas Menis-Mastromichalakis, Giorgos Filandrianos, Jason Liartis +2
As machine learning (ML) models and datasets increase in complexity, the demand for methods that enhance explainability and interpretability becomes paramount. Prototypes, by encap…
Beyond One-Size-Fits-All: Adapting Counterfactual Explanations to User Objectives
Orfeas Menis Mastromichalakis, Jason Liartis, Giorgos Stamou
Explainable Artificial Intelligence (XAI) has emerged as a critical area of research aimed at enhancing the transparency and interpretability of AI systems. Counterfactual Explanat…
Synergy of Machine and Deep Learning Models for Multi-Painter Recognition
Vassilis Lyberatos, Paraskevi-Antonia Theofilou, Jason Liartis +1
The growing availability of digitized art collections has created the need to manage, analyze and categorize large amounts of data related to abstract concepts, highlighting a dema…