From Graphs to Gradients: Physics-Inspired Structural Attribution for Cyber-Phys

arXiv:2604.15898v1 Announce Type: new Abstract: For around a decade, non-symbolic methods have been the option of choice when explaining complex machine learning (ML) models.

arXiv:2608.12555v1 Announce Type: new Abstract: Predictive explanation methods attribute a model output; they do not, by themselves, attribute an intervention effect on the

arXiv:2606.15273v1 Announce Type: new Abstract: Shapley value-based feature attribution methods face challenges in scenarios involving complex feature interactions and causal

arXiv:2603.25001v1 Announce Type: new Abstract: Failure attribution is essential for diagnosing and improving multi-agent systems (MAS), yet existing benchmarks and methods