Our paper “PRISM: A Training System to Unlock the Potential of Temporal Graph Learning Through Staleness Avoidance” has been accepted at VLDB 2026. PRISM tackles memory staleness in TGNN training using multi-version memory and iterative memory refinement, improving model accuracy and training/inference efficiency without changing the model itself. Congratulations to Emon and all co-authors!