@misc{p28,
  title = {SeLMRoute: Probabilistic Semantic Evidence for Large Language Model Routing},
  author = {Vasilis Perifanis and Nikolaos Pavlidis and Symeon Symeonidis},
  year = {2026},
  url = {https://arxiv.org/abs/2609.34736},
  doi = {10.48550/arXiv.2609.34736},
  howpublished = {arXiv:2609.34736}
}

@inproceedings{p27,
  title = {Federated Learning for Electric Vehicle Energy Demand Prediction Across Distributed Users},
  author = {Vasilis Perifanis and Foteini Nikolaidou and Panagiotis Thomakos and Nikolaos Pavlidis and Andreas Sendros and Ignacio Lacalle Úbeda and Felix Mondl and Michael Glensvig},
  year = {2027},
  url = {https://link.springer.com/chapter/10.1007/978-3-032-37218-5_11},
  doi = {10.1007/978-3-032-37218-5_11},
  booktitle = {Availability, Reliability and Security: ARES 2026 EU Projects Symposium Workshops, LNCS 16903, pp. 166-184}
}

@article{p26,
  title = {Explainable machine learning for non-technical loss detection in power systems},
  author = {Nikolaos Pavlidis and Christos L Athanasiadis and Vasileios Perifanis and Pavlos S Efraimidis and Theofilos A Papadopoulos},
  year = {2026},
  url = {https://www.sciencedirect.com/science/article/pii/S2352467726003619},
  doi = {10.1016/j.segan.2026.102479},
  journal = {Sustainable Energy, Grids and Networks 47, 102479}
}

@misc{p25,
  title = {Federated Learning for Early Prediction of EV Charging Demand},
  author = {Vasilis Perifanis and Foteini Nikolaidou and Nikolaos Pavlidis and Panagiotis Thomakos and Andreas Sendros},
  year = {2026},
  url = {https://arxiv.org/abs/2605.04993},
  doi = {10.48550/arXiv.2605.04993},
  howpublished = {arXiv:2605.04993}
}

@inproceedings{p24,
  title = {DUTH at EXIST 2025: Multilingual Sexism Detection with Soft Labels and Transformers.},
  author = {Georgios Arampatzis and Vasileios Perifanis and Symeon Symeonidis and Avi Arampatzis},
  year = {2025},
  url = {https://ceur-ws.org/Vol-4038/paper_140.pdf},
  booktitle = {CLEF 2025 Working Notes, CEUR Workshop Proceedings 4038, 1793-1800}
}

@article{p23,
  title = {Federated learning for privacy-friendly health apps: a case study on ovulation tracking},
  author = {Nikolaos Pavlidis and Andreas Sendros and Theodoros Tsiolakis and Periklis Kostamis and Christos Karasoulas and Eleni Briola and Christos Chrysanthos Nikolaidis and Vasilis Perifanis and George Drosatos and Eleftheria Katsiri and Despoina Elisavet Filippidou and Anastasios Manos and Pavlos S Efraimidis},
  year = {2025},
  url = {https://www.mdpi.com/2224-2708/14/1/11},
  doi = {10.3390/jsan14010011},
  journal = {Journal of Sensor and Actuator Networks 14(1), 11}
}

@article{p22,
  title = {Evaluation of bio-inspired models under different learning settings for energy efficiency in network traffic prediction},
  author = {Theodoros Tsiolakis and Nikolaos Pavlidis and Vasileios Perifanis and Pavlos Efraimidis},
  year = {2025},
  url = {https://www.worldscientific.com/doi/abs/10.1142/S0129065725500583},
  doi = {10.1142/S0129065725500583},
  journal = {International Journal of Neural Systems 35(12), 2550058}
}

@misc{p21,
  title = {Evaluating the Defense Potential of Machine Unlearning against Membership Inference Attacks},
  author = {Theodoros Tsiolakis and Vasilis Perifanis and Nikolaos Pavlidis and Christos Chrysanthos Nikolaidis and Aristeidis Sidiropoulos and Pavlos S Efraimidis},
  year = {2025},
  url = {https://arxiv.org/abs/2508.16150},
  doi = {10.48550/arXiv.2508.16150},
  howpublished = {arXiv:2508.16150}
}

@incollection{p20,
  title = {Federated Learning for Recommender Systems: Advances and Perspectives},
  author = {Vasileios Perifanis and Nikolaos Pavlidis and Andreas Sendros and Pavlos S Efraimidis},
  year = {2025},
  url = {https://link.springer.com/chapter/10.1007/978-3-031-78841-3_5},
  doi = {10.1007/978-3-031-78841-3_5},
  booktitle = {Federated Learning Systems: Towards Privacy-Preserving Distributed AI, pp. 87-106}
}

@inproceedings{p19,
  title = {Large Language Models as Universal Predictors? An Empirical Study on Small Tabular Datasets},
  author = {Nikolaos Pavlidis and Vasilis Perifanis and Symeon Symeonidis and Pavlos S Efraimidis},
  year = {2026},
  url = {https://link.springer.com/chapter/10.1007/978-3-032-19865-5_8},
  doi = {10.1007/978-3-032-19865-5_8},
  booktitle = {Model and Data Engineering, MEDI 2025, pp. 109-116}
}

@inproceedings{p18,
  title = {Bridging the Gap: Challenges and Limitations of Federated Learning in Real-World Applications},
  author = {Vasilis Perifanis and Nikolaos Pavlidis and Foteini Nikolaidou and Despoina Kampouri and Pavlos S Efraimidis},
  year = {2025},
  url = {https://ieeexplore.ieee.org/abstract/document/11091634/},
  booktitle = {2025 10th International Conference on Smart and Sustainable Technologies (SpliTech), pp. 1-6}
}

@inproceedings{p17,
  title = {Justification Retrieval with LLMs, Retrieval-Augmented Generation, and Hybrid Labels},
  author = {Georgios Arampatzis and Vasileios Perifanis and Avi Arampatzis},
  year = {2025},
  url = {https://trec.nist.gov/pubs/trec34/papers/DUTH.rag.pdf},
  booktitle = {Proceedings of the 34th Text REtrieval Conference (TREC 2025)}
}

@misc{p16,
  title = {Federated Learning in Real-World Applications: Mitigating the Data Availability Problem},
  author = {Nikolaos Pavlidis and Theodoros Tsiolakis and Vasileios Perifanis and Pavlos S Efraimidis},
  year = {2025},
  url = {https://www.researchgate.net/publication/388225568_Federated_Learning_in_Real-World_Applications_Mitigating_the_Data_Availability_Problem},
  howpublished = {Author-posted position paper}
}

@inproceedings{p15,
  title = {A federated explainable ai model for breast cancer classification},
  author = {Eleni Briola and Christos Chrysanthos Nikolaidis and Vasileios Perifanis and Nikolaos Pavlidis and Pavlos Efraimidis},
  year = {2024},
  url = {https://dl.acm.org/doi/abs/10.1145/3655693.3660255},
  doi = {10.1145/3655693.3660255},
  booktitle = {European Interdisciplinary Cybersecurity Conference (EICC 2024), 194-201}
}

@article{p14,
  title = {Federated learning in mobile networks: A comprehensive case study on traffic forecasting},
  author = {Nikolaos Pavlidis and Vasileios Perifanis and Selim F Yilmaz and Francesc Wilhelmi and Marco Miozzo and Pavlos S Efraimidis and Remous-Aris Koutsiamanis and Pavol Mulinka and Paolo Dini},
  year = {2025},
  url = {https://ieeexplore.ieee.org/abstract/document/10759814/},
  doi = {10.1109/TSUSC.2024.3504242},
  journal = {IEEE Transactions on Sustainable Computing, 10(3), 576-587}
}

@misc{p13,
  title = {Federated Anomaly Detection for Early-Stage Diagnosis of Autism Spectrum Disorders using Serious Game Data},
  author = {Nikolaos Pavlidis and Vasileios Perifanis and Eleni Briola and Christos-Chrysanthos Nikolaidis and Eleftheria Katsiri and Pavlos S Efraimidis and Despina Elisabeth Filippidou},
  year = {2024},
  url = {https://arxiv.org/abs/2410.20003},
  doi = {10.48550/arXiv.2410.20003},
  howpublished = {arXiv:2410.20003}
}

@inproceedings{p12,
  title = {Towards Detecting Non-Technical Losses in Electrical Power Systems with Machine Learning},
  author = {Vasilis Perifanis and Christos L Athanasiadis and Nikolaos Pavlidis and Pavlos S Efraimidis and Theofilos A Papadopoulos},
  year = {2024},
  url = {https://ieeexplore.ieee.org/abstract/document/10799450/},
  doi = {10.1109/SyNERGYMED62435.2024.10799450},
  booktitle = {Energy Transition in the Mediterranean Area (SyNERGY MED 2024), 1-5}
}

@inproceedings{p11,
  title = {Carbon-Aware Machine Learning: A Case Study on Cellular Traffic Forecasting with Spiking Neural Networks},
  author = {Theodoros Tsiolakis and Nikolaos Pavlidis and Vasileios Perifanis and Pavlos S Efraimidis},
  year = {2024},
  url = {https://link.springer.com/chapter/10.1007/978-3-031-63219-8_14},
  doi = {10.1007/978-3-031-63219-8_14},
  booktitle = {Artificial Intelligence Applications and Innovations (AIAI 2024), 178-191}
}

@inproceedings{p10,
  title = {SFTC: Machine Unlearning via Selective Fine-tuning and Targeted Confusion},
  author = {Vasileios Perifanis and Efstathios Karypidis and Nikos Komodakis and Pavlos Efraimidis},
  year = {2024},
  url = {https://dl.acm.org/doi/abs/10.1145/3655693.3655697},
  doi = {10.1145/3655693.3655697},
  booktitle = {European Interdisciplinary Cybersecurity Conference (EICC 2024), 29-36}
}

@article{p09,
  title = {Federated learning for 5G base station traffic forecasting},
  author = {Vasileios Perifanis and Nikolaos Pavlidis and Remous-Aris Koutsiamanis and Pavlos S Efraimidis},
  year = {2023},
  url = {https://www.sciencedirect.com/science/article/pii/S138912862300395X},
  doi = {10.1016/j.comnet.2023.109950},
  journal = {Computer Networks, 235, 109950}
}

@inproceedings{p08,
  title = {Towards Energy-Aware Federated Traffic Prediction for Cellular Networks},
  author = {Vasileios Perifanis and Nikolaos Pavlidis and Selim F Yilmaz and Francesc Wilhelmi and Elia Guerra and Marco Miozzo and Pavlos S Efraimidis and Paolo Dini and Remous-Aris Koutsiamanis},
  year = {2023},
  url = {https://ieeexplore.ieee.org/abstract/document/10306017/},
  doi = {10.1109/FMEC59375.2023.10306017},
  booktitle = {Fog and Mobile Edge Computing (FMEC 2023), 93-100}
}

@inproceedings{p07,
  title = {Intelligent client selection for federated learning using cellular automata},
  author = {Nikolaos Pavlidis and Vasileios Perifanis and Theodoros Panagiotis Chatzinikolaou and Georgios Ch Sirakoulis and Pavlos S Efraimidis},
  year = {2023},
  url = {https://ieeexplore.ieee.org/abstract/document/10652769/},
  doi = {10.1109/CNNA60945.2023.10652769},
  booktitle = {Cellular Nanoscale Networks and their Applications (CNNA 2023), 1-4}
}

@inproceedings{p06,
  title = {DUTH at SemEval-2023 Task 9: An Ensemble Approach for Twitter Intimacy Analysis},
  author = {Giorgos Arampatzis and Vasileios Perifanis and Symeon Symeonidis and Avi Arampatzis},
  year = {2023},
  url = {https://aclanthology.org/2023.semeval-1.170/},
  doi = {10.18653/v1/2023.semeval-1.170},
  booktitle = {SemEval-2023, 1225-1230}
}

@inproceedings{p05,
  title = {Federated Learning for Early Dropout Prediction on Healthy Ageing Applications},
  author = {Christos Chrysanthos Nikolaidis and Vasileios Perifanis and Nikolaos Pavlidis and Pavlos S Efraimidis},
  year = {2023},
  url = {https://ieeexplore.ieee.org/abstract/document/10306129/},
  doi = {10.1109/FMEC59375.2023.10306129},
  booktitle = {Fog and Mobile Edge Computing (FMEC 2023), 135-142}
}

@inproceedings{p04,
  title = {An Extensive Overview of Feature Representation Techniques for Molecule Classification},
  author = {Nikolaos Pavlidis and Christos Chrysanthos Nikolaidis and Vasileios Perifanis and Anastasia Papadopoulou and Pavlos Efraimidis and Avi Arampatzis},
  year = {2023},
  url = {https://dl.acm.org/doi/abs/10.1145/3635059.3635083},
  doi = {10.1145/3635059.3635083},
  booktitle = {Pan-Hellenic Conference on Progress in Computing and Informatics (PCI 2023), 156-162}
}

@misc{p03,
  title = {Predicting Early Dropouts of an Active and Healthy Ageing App},
  author = {Vasileios Perifanis and Ioanna Michailidi and Giorgos Stamatelatos and George Drosatos and Pavlos S Efraimidis},
  year = {2023},
  url = {https://arxiv.org/abs/2308.00539},
  doi = {10.48550/arXiv.2308.00539},
  howpublished = {arXiv:2308.00539}
}

@article{p02,
  title = {FedPOIRec: Privacy-Preserving Federated POI Recommendation with Social Influence},
  author = {Vasileios Perifanis and George Drosatos and Giorgos Stamatelatos and Pavlos S Efraimidis},
  year = {2023},
  url = {https://www.sciencedirect.com/science/article/pii/S0020025522015171},
  doi = {10.1016/j.ins.2022.12.024},
  journal = {Information Sciences, 623, 767-790}
}

@article{p01,
  title = {Federated Neural Collaborative Filtering},
  author = {Vasileios Perifanis and Pavlos S Efraimidis},
  year = {2022},
  url = {https://www.sciencedirect.com/science/article/pii/S0950705122001812},
  doi = {10.1016/j.knosys.2022.108441},
  journal = {Knowledge-Based Systems, 242, 108441}
}