output
19982026
most citedClustering and Community Detection in Directed Networks: A Survey

599 citations

250 papers

cs.LG2026

Greening AI Inference with Accuracy and Latency-aware User Incentives

Vasilios A. Siris, Adamantia Stamou, George D. Stamoulis +2

The widespread use of AI services has raised concerns for its environmental sustainability, towards which recent studies have identified carbon emissions of AI inference as the maj…

cs.CR2026

WOOTdroid: Whole-system Online On-device Tracing for Android

Simon Althaus, Nikolaos Alexopoulos, Max Mühlhäuser +2

System auditing on Android faces two problems. First, existing syscall tracers lose events under load, silently overwriting entries faster than a user space reader can drain them.…

cs.SE2026

Awakening: Modern Challenges and Opportunities of Software Engineering Research

Diomidis Spinellis, Zoe Kotti

Software engineering research benefited for decades from openly available tools, accessible systems, and problems that could be studied at modest scale. Today, many of the most rel…

cs.SE2026★ 1 cited

Source Code Hotspots: A Diagnostic Method for Quality Issues

Saleha Muzammil, Mughees Ur Rehman, Zoe Kotti +1

Software source code often harbours "hotspots": small portions of the code that change far more often than the rest of the project and thus concentrate maintenance activity. We min…

cs.DC2026

SCRamble: Adaptive Decentralized Overlay Construction for Blockchain Networks

Evangelos Kolyvas, Alexandros Antonov, Spyros Voulgaris

Despite being under development for over 15 years, transaction throughput remains one of the key challenges confronting blockchains, which typically has a cap of a limited number o…

cs.SE2025

PyTrim: A Practical Tool for Reducing Python Dependency Bloat

Konstantinos Karakatsanis, Georgios Alexopoulos, Ioannis Karyotakis +4

Dependency bloat is a persistent challenge in Python projects, which increases maintenance costs and security risks. While numerous tools exist for detecting unused dependencies in…

cs.LG2025

Adaptive Out-of-Control Point Pattern Detection in Sequential Random Finite Set Observations

Konstantinos Bourazas, Savvas Papaioannou, Panayiotis Kolios

In this work we introduce a novel adaptive anomaly detection framework specifically designed for monitoring sequential random finite set (RFS) observations. Our approach effectivel…

cs.CL2025

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…

cs.CR2025★ 1 cited

From Permissioned to Proof-of-Stake Consensus

Jovan Komatovic, Andrew Lewis-Pye, Joachim Neu +2

This paper presents the first generic compiler that transforms any permissioned consensus protocol into a proof-of-stake permissionless consensus protocol. For each of the followin…

cs.CL2025

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…

eess.SP2025★ 2 cited

A comprehensive review of sensor technologies, instrumentation, and signal processing solutions for low-power Internet of Things systems with mini-computing devices

Alexandros Gazis, Ioannis Papadongonas, Athanasios Andriopoulos +2

This article provides a comprehensive overview of sensors commonly used in low-cost, low-power systems, focusing on key concepts such as Internet of Things (IoT), Big Data, and sma…

cs.GT2024

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.…

cs.SE2024★ 6 cited

A Systematic Literature Review on a Decade of Industrial TLA+ Practice

Roman Bögli, Leandro Lerena, Christos Tsigkanos +1

TLA+ is a formal specification language used for designing, modeling, documenting, and verifying systems through model checking. Despite significant interest from the research comm…

stat.ME2024

Bayesian Cluster Weighted Gaussian Models

Panagiotis Papastamoulis, Konstantinos Perrakis

We introduce a novel class of Bayesian mixtures for normal linear regression models which incorporates a further Gaussian random component for the distribution of the predictor var…

cs.SE2024★ 1 cited

Broken Windows: Exploring the Applicability of a Controversial Theory on Code Quality

Diomidis Spinellis, Panos Louridas, Maria Kechagia +1

Is the quality of existing code correlated with the quality of subsequent changes? According to the (controversial) broken windows theory, which inspired this study, disorder sets…

cs.CL2024★ 1 cited

Local Explanations and Self-Explanations for Assessing Faithfulness in black-box LLMs

Christos Fragkathoulas, Odysseas S. Chlapanis

This paper introduces a novel task to assess the faithfulness of large language models (LLMs) using local perturbations and self-explanations. Many LLMs often require additional co…

stat.AP2024

Stable Survival Extrapolation via Transfer Learning

Anastasios Apsemidis, Nikolaos Demiris

The mean survival is the key ingredient of the decision process in several applications, notably in health economic evaluations. It is defined as the area under the complete surviv…

stat.ME2024★ 1 cited

Directional data analysis using the spherical Cauchy and the Poisson kernel-based distribution

Michail Tsagris, Panagiotis Papastamoulis, Shogo Kato

In 2020, two novel distributions for the analysis of directional data were introduced: the spherical Cauchy distribution and the Poisson kernel-based distribution. This paper provi…

math.NA2024★ 3 cited

Fredholm Neural Networks

Kyriakos Georgiou, Constantinos Siettos, Athanasios N. Yannacopoulos

Within the family of explainable machine-learning, we present Fredholm neural networks (Fredholm NNs): deep neural networks (DNNs) architectures motivated by fixed-point iteration…

cs.GT2024

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…

cs.CL2024★ 2 cited

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…

cs.LG2024★ 20 cited

RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators

Gianluca Fabiani, Ioannis G. Kevrekidis, Constantinos Siettos +1

Deep Operator Networks (DeepOnets) have revolutionized the domain of scientific machine learning for the solution of the inverse problem for dynamical systems. However, their imple…

stat.ME2024★ 7 cited

A Model-Based Approach to Shot Charts Estimation in Basketball

Luca Scrucca, Dimitris Karlis

Shot charts in basketball analytics provide an indispensable tool for evaluating players' shooting performance by visually representing the distribution of field goal attempts acro…

cs.LG2024★ 3 cited

GLANCE: Global Actions in a Nutshell for Counterfactual Explainability

Loukas Kavouras, Eleni Psaroudaki, Konstantinos Tsopelas +9

The widespread deployment of machine learning systems in critical real-world decision-making applications has highlighted the urgent need for counterfactual explainability methods…