181 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National Technical University of AthensGR18 papers
- National and Kapodistrian University of AthensGR16 papers
- Democritus University of ThraceGR10 papers
- Athens University of Economics and BusinessGR9 papers
- University of PiraeusGR9 papers
- Centre National de la Recherche ScientifiqueFR7 papers
- Archimedia (Greece)GR5 papers
- National Observatory of AthensGR5 papers
- University of PeloponneseGR5 papers
- Astronomical Observatory of CapodimonteIT4 papers
- Czech Technical University in PragueCZ4 papers
- European Space Astronomy CentreES4 papers
96 papers
Overview of BioASQ 2026: The fourteenth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering
Anastasios Nentidis, Georgios Katsimpras, Anastasia Krithara +18
This paper presents an overview of the fourteenth edition of the BioASQ challenge, organized in the context of the Conference and Labs of the Evaluation Forum (CLEF) 2026. BioASQ i…
Incorporating Structure and Chord Constraints in Symbolic Transformer-based Melodic Harmonization
Maximos Kaliakatsos-Papakostas, Konstantinos Soiledis, Theodoros Tsamis +3
Transformer architectures offer significant advantages regarding the generation of symbolic music; their capabilities for incorporating user preferences toward what they generate i…
Contractive kinetic Langevin samplers beyond global Lipschitz continuity
Iosif Lytras, Panayotis Mertikopoulos
In this paper, we examine the problem of sampling from log-concave distributions with (possibly) superlinear gradient growth under kinetic (underdamped) Langevin algorithms. Using…
9th Workshop on Sign Language Translation and Avatar Technologies (SLTAT 2025)
Fabrizio Nunnari, Cristina Luna Jiménez, Rosalee Wolfe +5
The Sign Language Translation and Avatar Technology (SLTAT) workshops continue a series of gatherings to share recent advances in improving deaf / human communication through non-i…
CultureMERT: Continual Pre-Training for Cross-Cultural Music Representation Learning
Angelos-Nikolaos Kanatas, Charilaos Papaioannou, Alexandros Potamianos
Recent advances in music foundation models have improved audio representation learning, yet their effectiveness across diverse musical traditions remains limited. We introduce Cult…
Only-Style: Stylistic Consistency in Image Generation without Content Leakage
Tilemachos Aravanis, Panagiotis Filntisis, Petros Maragos +1
Generating images in a consistent reference visual style remains a challenging computer vision task. State-of-the-art methods aiming for style-consistent generation struggle to eff…
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…
ConspEmoLLM-v2: A robust and stable model to detect sentiment-transformed conspiracy theories
Zhiwei Liu, Paul Thompson, Jiaqi Rong +1
Despite the many benefits of large language models (LLMs), they can also cause harm, e.g., through automatic generation of misinformation, including conspiracy theories. Moreover,…
Open and Sustainable AI: challenges, opportunities and the road ahead in the life sciences (October 2025 -- Version 2)
Gavin Farrell, Eleni Adamidi, Rafael Andrade Buono +27
Artificial intelligence (AI) has recently seen transformative breakthroughs in the life sciences, expanding possibilities for researchers to interpret biological information at an…
Landscape Complexity for the Empirical Risk of Generalized Linear Models: Discrimination between Structured Data
Theodoros G. Tsironis, Aris L. Moustakas
We use the Kac-Rice formula and results from random matrix theory to obtain the average number of critical points of a family of high-dimensional empirical loss functions, where th…
Revisiting Medical Image Retrieval via Knowledge Consolidation
Yang Nan, Huichi Zhou, Xiaodan Xing +5
As artificial intelligence and digital medicine increasingly permeate healthcare systems, robust governance frameworks are essential to ensure ethical, secure, and effective implem…
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…
FRAUD-RLA: A new reinforcement learning adversarial attack against credit card fraud detection
Daniele Lunghi, Yannick Molinghen, Alkis Simitsis +2
Adversarial attacks pose a significant threat to data-driven systems, and researchers have spent considerable resources studying them. Despite its economic relevance, this trend la…
Can LLMs Predict Citation Intent? An Experimental Analysis of In-context Learning and Fine-tuning on Open LLMs
Paris Koloveas, Serafeim Chatzopoulos, Thanasis Vergoulis +1
This work investigates the ability of open Large Language Models (LLMs) to predict citation intent through in-context learning and fine-tuning. Unlike traditional approaches relyin…
On the Tractability Landscape of the Conditional Minisum Approval Voting Rule
Georgios Amanatidis, Michael Lampis, Evangelos Markakis +1
This work examines the Conditional Approval Framework for elections involving multiple interdependent issues, specifically focusing on the Conditional Minisum Approval Voting Rule.…
Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems
Daniel Gibert, Nikolaos Totosis, Constantinos Patsakis +2
The proliferation of malware, particularly through the use of packing, presents a significant challenge to static analysis and signature-based malware detection techniques. The app…
Motion-prior Contrast Maximization for Dense Continuous-Time Motion Estimation
Friedhelm Hamann, Ziyun Wang, Ioannis Asmanis +3
Current optical flow and point-tracking methods rely heavily on synthetic datasets. Event cameras are novel vision sensors with advantages in challenging visual conditions, but sta…
Pandora's Box Problem With Time Constraints
Georgios Amanatidis, Ben Berger, Tomer Ezra +4
The Pandora's Box problem models the search for the best alternative when evaluation is costly. In the simplest variant, a decision maker is presented with boxes, each associat…
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…
ViG-Bias: Visually Grounded Bias Discovery and Mitigation
Badr-Eddine Marani, Mohamed Hanini, Nihitha Malayarukil +3
The proliferation of machine learning models in critical decision making processes has underscored the need for bias discovery and mitigation strategies. Identifying the reasons be…
Streamline Intelligent Crowd Monitoring with IoT Cloud Computing Middleware
Alexandros Gazis, Eleftheria Katsiri
This article introduces a novel middleware that utilizes cost-effective, low-power computing devices like Raspberry Pi to analyze data from wireless sensor networks (WSNs). It is d…
Tamed Langevin sampling under weaker conditions
Iosif Lytras, Panayotis Mertikopoulos
Motivated by applications to deep learning which often fail standard Lipschitz smoothness requirements, we examine the problem of sampling from distributions that are not log-conca…
Directed Metric Structures arising in Large Language Models
Stéphane Gaubert, Yiannis Vlassopoulos
Large Language Models are transformer neural networks which are trained to produce a probability distribution on the possible next words to given texts in a corpus, in such a way t…
Fairness in Ranking: Robustness through Randomization without the Protected Attribute
Andrii Kliachkin, Eleni Psaroudaki, Jakub Marecek +1
There has been great interest in fairness in machine learning, especially in relation to classification problems. In ranking-related problems, such as in online advertising, recomm…