55 citations · 130 across the 15 of their papers we have counts for
17 papers
From Tokens to Watt-hours: Analytical Energy Estimation for LLM Inference on Modern GPUs
Tina Vartziotis, Rodopi Kosteli, Elli Vartziotis +5
The operational energy consumption of large language model (LLM) inference is becoming an increasingly important component of the environmental footprint of deployed AI systems. Ho…
GreekMMLU: A Native-Sourced Multitask Benchmark for Evaluating Language Models in Greek
Yang Zhang, Mersin Konomi, Christos Xypolopoulos +6
Large Language Models (LLMs) are commonly trained on multilingual corpora that include Greek, yet reliable evaluation benchmarks for Greek-particularly those based on authentic, na…
CSE-UOI at SemEval-2026 Task 6: A Two-Stage Heterogeneous Ensemble with Deliberative Complexity Gating for Political Evasion Detection
Christos Tzouvaras, Konstantinos Skianis, Athanasios Voulodimos
This paper describes our system for SemEval-2026 Task 6, which classifies clarity of responses in political interviews into three categories: Clear Reply, Ambivalent, and Clear Non…
A Greek Government Decisions Dataset for Public-Sector Analysis and Insight
Giorgos Antoniou, Giorgos Filandrianos, Aggelos Vlachos +4
We introduce an open, machine-readable corpus of Greek government decisions sourced from the national transparency platform Diavgeia. The resource comprises 1 million decisions, fe…
KGRAG-Ex: Explainable Retrieval-Augmented Generation with Knowledge Graph-based Perturbations
Georgios Balanos, Evangelos Chasanis, Konstantinos Skianis +1
Retrieval-Augmented Generation (RAG) enhances language models by grounding responses in external information, yet explainability remains a critical challenge, particularly when ret…
On the Lipschitz Continuity of Set Aggregation Functions and Neural Networks for Sets
Giannis Nikolentzos, Konstantinos Skianis
The Lipschitz constant of a neural network is connected to several important properties of the network such as its robustness and generalization. It is thus useful in many settings…
Leveraging LLMs for Translating and Classifying Mental Health Data
Konstantinos Skianis, A. Seza Doğruöz, John Pavlopoulos
Large language models (LLMs) are increasingly used in medical fields. In mental health support, the early identification of linguistic markers associated with mental health conditi…
Graph Reasoning with Large Language Models via Pseudo-code Prompting
Konstantinos Skianis, Giannis Nikolentzos, Michalis Vazirgiannis
Large language models (LLMs) have recently achieved remarkable success in various reasoning tasks in the field of natural language processing. This success of LLMs has also motivat…
Building Multilingual Datasets for Predicting Mental Health Severity through LLMs: Prospects and Challenges
Konstantinos Skianis, John Pavlopoulos, A. Seza Doğruöz
Large Language Models (LLMs) are increasingly being integrated into various medical fields, including mental health support systems. However, there is a gap in research regarding t…
On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks
Jhony H. Giraldo, Konstantinos Skianis, Thierry Bouwmans +1
Graph Neural Networks (GNNs) have succeeded in various computer science applications, yet deep GNNs underperform their shallow counterparts despite deep learning's success in other…
Towards Fine-Dining Recipe Generation with Generative Pre-trained Transformers
Konstantinos Katserelis, Konstantinos Skianis
Food is essential to human survival. So much so that we have developed different recipes to suit our taste needs. In this work, we propose a novel way of creating new, fine-dining…
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…
Rep the Set: Neural Networks for Learning Set Representations
Konstantinos Skianis, Giannis Nikolentzos, Stratis Limnios +1
In several domains, data objects can be decomposed into sets of simpler objects. It is then natural to represent each object as the set of its components or parts. Many conventiona…
Word Embeddings from Large-Scale Greek Web Content
Stamatis Outsios, Konstantinos Skianis, Polykarpos Meladianos +2
Word embeddings are undoubtedly very useful components in many NLP tasks. In this paper, we present word embeddings and other linguistic resources trained on the largest to date di…
Orthogonal Matching Pursuit for Text Classification
Konstantinos Skianis, Nikolaos Tziortziotis, Michalis Vazirgiannis
In text classification, the problem of overfitting arises due to the high dimensionality, making regularization essential. Although classic regularizers provide sparsity, they fail…
GraKeL: A Graph Kernel Library in Python
Giannis Siglidis, Giannis Nikolentzos, Stratis Limnios +3
The problem of accurately measuring the similarity between graphs is at the core of many applications in a variety of disciplines. Graph kernels have recently emerged as a promisin…
Kernel Graph Convolutional Neural Networks
Giannis Nikolentzos, Polykarpos Meladianos, Antoine Jean-Pierre Tixier +2
Graph kernels have been successfully applied to many graph classification problems. Typically, a kernel is first designed, and then an SVM classifier is trained based on the featur…