3 papers
cs.LG2025
On the Occurence of Critical Learning Periods in Neural Networks
Stanisław Pawlak
This study delves into the plasticity of neural networks, offering empirical support for the notion that critical learning periods and warm-starting performance loss can be avoided…
cs.LG2025
Backdoor Vectors: a Task Arithmetic View on Backdoor Attacks and Defenses
Stanisław Pawlak, Jan Dubiński, Daniel Marczak +1
Model merging (MM) recently emerged as an effective method for combining large deep learning models. However, it poses significant security risks. Recent research shows that it is…
cs.CR2025
Addressing The Devastating Effects Of Single-Task Data Poisoning In Exemplar-Free Continual Learning
Stanisław Pawlak, Bartłomiej Twardowski, Tomasz Trzciński +1
Our research addresses the overlooked security concerns related to data poisoning in continual learning (CL). Data poisoning - the intentional manipulation of training data to affe…