The aggregated attention mechanism in M (B) N a (Fig. ) also appears more fine-tuned, with greater weights on the latest cycle data, which is consistent with its precise predictions. While M (P ) N a is adaptable, it shows a marginally wider uncertainty (Fig. ). Available Input Cycles Available Input Cycles Available Input Cycles Available Input Cycles and) depict the predictions for voltage drop, CE and Q dis against the ground truth. The colorbar here shows the aggregated attention weights across the input data. Plots e-g) provide a detailed logarithmic sensitivity analysis per predictive cycle for each input parameter, and plots h-j) aggregate these sensitivities, highlighting the model's focus on different input cycles, especially the most recent ones, reflecting M (B) N a 's protocol adaptability and robust response to experimental noise.