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cs.AI2025
Large Language Models as Universal Predictors? An Empirical Study on Small Tabular Datasets
Nikolaos Pavlidis, Vasilis Perifanis, Symeon Symeonidis +1
Large Language Models (LLMs), originally developed for natural language processing (NLP), have demonstrated the potential to generalize across modalities and domains. With their in…
cs.CR2025
Evaluating the Defense Potential of Machine Unlearning against Membership Inference Attacks
Theodoros Tsiolakis, Vasilis Perifanis, Nikolaos Pavlidis +3
Membership Inference Attacks (MIAs) pose a significant privacy risk by enabling adversaries to determine if a specific data point was part of a model's training set. This work empi…