Modeling stochastic dynamical systems remains a central challenge across disciplines. Incomplete knowledge of nonlinear interactions and state-dependent fluctuations often renders bottom-up approaches ineffective, motivating methods that infer governing equations directly from data. However, parametric models struggle...
G. Pillonetto, A. Giaretta, M. Bisiacco· Nature Communications· 0 citations
In embodied cyber-physical systems, active cyberattacks pose an immediate threat not just to data, but to physical integrity and human safety. While existing security approaches excel at detection, they lack the runtime mechanisms to determine whether a disruption is tolerable or if performance degradation remains with...
Gysella Imrell, E. Miotto, Mahya Mohammadi Kashani et al.· Proceedings of the 2026 8th...· 0 citations
Investigating Behavior Trees (BTs) as an alternative intermediate representation for LLM-based vulnerability detection suggests that BTs can provide a compact and useful structured representation for vulnerability detection with quantized, locally deployable LLMs.
Mechanical AutoDAN is introduced, a probe-guided variant of AutoDAN that replaces full-model fitness evaluation with partial forward passes and probe-based scoring inside a genetic prompt search loop, and it is found that refusal is linearly decodable well before the final layer, indicating that safety-relevant behavio...
M. G. Collu, Riccardo Conte, A. Giaretta et al.· arXiv.org· 1 citation
This paper claims that an in-depth investigation of the adversarial robustness of NeSy models is necessary and provides the first systematic evaluation of backdoor attacks against NeSy, and shows that while NeSy models are indeed more robust than their neural counterpart on average, their robustness vastly depend on th...
Marco Antonio Corallo, Andrea Agiollo, Mauro Conti et al.· 0 citations
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