In Fig. , M (B) N a shows a greater overall sensitivity across input cycles, particularly for the dimensions of voltage drop and Q dis . This is further illustrated in sensitivity profiles and cumulative plots (Fig. ) highlighting a refined input-response relationship and a lower uncertainty interval in the primary prediction (Fig. ). Such a distinct sensitivity indicates M (B) N a 's ability to precisely identify and respond to subtle variations. Despite the high experimental noise and limited battery performance, the saliency and attention trends of both models remain remarkably similar. This suggests that both mechanisms are intrinsic to the model's architecture, enabling them to perform consistently at diverse scenarios.