AI RESEARCH
SYNAPSE: Framework for Neuron Analysis and Perturbation in Sequence Encoding
arXiv CS.LG
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ArXi:2603.08424v1 Announce Type: new In recent years, Artificial Intelligence has become a powerful partner for complex tasks such as data analysis, prediction, and problem-solving, yet its lack of transparency raises concerns about its reliability. In sensitive domains such as healthcare or cybersecurity, ensuring transparency, trustworthiness, and robustness is essential, since the consequences of wrong decisions or successful attacks can be severe. Prior neuron-level interpretability approaches are primarily descriptive, task-dependent, or require re.