Temporal Memory-Aware Online Test-Time Adaptation on Dynamic Graphs

arXiv:2608.27948 · cs.LG · Submitted 2026-08-28 · Read on arXiv

cs.LG

Submitted: 2026-08-28

Updated: 2026-09-07

Terminology

• Adaptation — 92× in this paper · explained in 1 episode
• Consistency — 28× in this paper · explained in 3 episodes
• Distribution Shift — 25× in this paper · explained in 6 episodes
• Online Adaptation — 20× in this paper · explained in 3 episodes
• Generalization — 11× in this paper · explained in 13 episodes
• Robustness — 10× in this paper · explained in 5 episodes
• AUC — 9× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Temporal consistency — 7× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Representation Learning — 6× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 5× in this paper · explained in 5 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Adaptability — 3× in this paper · explained in 1 episode
• Pseudo-labels — 3× in this paper · explained in 2 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Continual Learning — 2× in this paper · explained in 2 episodes
• Domain Adaptation — 2× in this paper · explained in 5 episodes
• Model-Agnostic — 2× in this paper · explained in 2 episodes
• Pseudo-labeling — 2× in this paper · explained in 3 episodes
• Test-time Adaptation (TTA) — 2× in this paper · explained in 3 episodes
• Adjacency Matrix — 1× in this paper · explained in 1 episode
• Area Under the ROC Curve — 1× in this paper
• Computational overhead — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Graph Neural Network (GNN) — 1× in this paper · explained in 3 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Self-Supervised Learning (SSL) — 1× in this paper · explained in 4 episodes
• Semantic Drift — 1× in this paper · explained in 3 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Tent: Fully Test-time Adaptation by Entropy Minimization
• Towards Stable Test-Time Adaptation in Dynamic Wild World
• Test-Time Adaptation via Self-Training with Nearest Neighbor Information
• BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
• Empowering Graph Representation Learning with Test-Time Graph Transformation
• GraphTTA: Test Time Adaptation on Graph Neural Networks
• Inductive Representation Learning on Temporal Graphs
• Temporal Graph Networks for Deep Learning on Dynamic Graphs
• Do We Really Need Complicated Model Architectures For Temporal Networks?

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