Mass‑Aware Attention preserves evidence lost to softmax, boosting temporal graph performance
Standard softmax attention collapses repeated evidence, hiding structural cues in temporal graphs. The new Mass‑Aware Attention replaces L1 with an Lp norm that keeps the count of contributing inputs, raising future‑link AUC in 11/12 model‑dataset combos and sharpening recovery of basic graph statistics without extra parameters.