11 citations · 22 across the 7 of their papers we have counts for
8 papers
A Comparative Study of Counterfactual Explainers for Graph Neural Networks Enabling Multiple Types of Graph Edit
Maria Myrto Villia, Filippos Gouidis, Theodore Patkos +1
Counterfactual explanations for graph-structured data seek to determine minimal and realistic modifications required in an input graph to alter a model's prediction to a predefined…
A Comparative Evaluation of Embeddings and LLMs in a Greek Book Publisher Setting - The CUP Dataset
Katerina Papantoniou, Panagiotis Papadakos, Theodore Patkos +3
We present CUP, a Greek book retrieval benchmark consisting of 868 catalog records and 104 expert-annotated queries with graded relevance judgments. We evaluate sparse (BM25), dens…
A Completion-Aware Framework for Impactful Counterfactual Explainability in Graph Neural Networks
Maria Myrto Villia, Filippos Gouidis, Theodore Patkos +1
In this study, we propose a novel pipeline for generic, model-agnostic, local-level counterfactual explainability in graph neural networks (GNNs). Although counterfactual explainer…
Recognizing Unseen States of Unknown Objects by Leveraging Knowledge Graphs
Filipos Gouidis, Konstantinos Papoutsakis, Theodore Patkos +2
We investigate the problem of Object State Classification (OSC) as a zero-shot learning problem. Specifically, we propose the first Object-agnostic State Classification (OaSC) meth…
Deception detection in text and its relation to the cultural dimension of individualism/collectivism
Katerina Papantoniou, Panagiotis Papadakos, Theodore Patkos +3
Deception detection is a task with many applications both in direct physical and in computer-mediated communication. Our focus is on automatic deception detection in text across cu…
A Review on Intelligent Object Perception Methods Combining Knowledge-based Reasoning and Machine Learning
Filippos Gouidis, Alexandros Vassiliades, Theodore Patkos +3
Object perception is a fundamental sub-field of Computer Vision, covering a multitude of individual areas and having contributed high-impact results. While Machine Learning has bee…
An Event Calculus Production Rule System for Reasoning in Dynamic and Uncertain Domains
Theodore Patkos, Dimitris Plexousakis, Abdelghani Chibani +1
Action languages have emerged as an important field of Knowledge Representation for reasoning about change and causality in dynamic domains. This article presents Cerbere, a produc…
Different Types of Conflicting Knowledge in AmI Environments
Martin Homola, Theodore Patkos
We characterize different types of conflicts that may occur in complex distributed multi-agent scenarios, such as in Ambient Intelligence (AmI) environments, and we argue that thes…