GAttNHP: Group Attention Neural Hawkes Process for Extrapolation Reasoning in Temporal Knowledge Graphs

arXiv:2607.14733 · cs.LG, stat.ML · Submitted 2026-07-16 · Read on arXiv

Xiangni Tian, Kaixian Yu, Runpeng Dai, Niansheng Tang, Hongtu Zhu

cs.LG, stat.ML

Submitted: 2026-07-16

Code: https://github.com/LiaoMengqi/KGMH

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Knowledge Graph — 27× in this paper · explained in 8 episodes
• Knowledge graphs — 17× in this paper · explained in 2 episodes
• Benchmark — 12× in this paper · explained in 2 episodes
• Non-Crossing Quantile — 10× in this paper
• Embeddings — 8× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Transformer — 6× in this paper · explained in 2 episodes
• Monotonicity — 4× in this paper · explained in 2 episodes
• Decoder — 3× in this paper · explained in 2 episodes
• Representation Learning — 3× in this paper · explained in 3 episodes
• Sparsity — 3× in this paper · explained in 5 episodes
• Ablation Study — 2× in this paper · explained in 3 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 3 episodes
• Calibration — 2× in this paper · explained in 9 episodes
• Mean Reciprocal Rank — 2× in this paper
• Multi-hop Reasoning — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 6 episodes
• Semantic Similarity — 2× in this paper · explained in 2 episodes
• Unified Framework — 2× in this paper · explained in 6 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Augmentation — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 9 episodes
• Data Augmentation — 1× in this paper · explained in 10 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Empirical Coverage — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 14 episodes
• Heavy-Tailed Distributions — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Mean Squared Error — 1× in this paper
• Overfitting — 1× in this paper · explained in 2 episodes
• Performance Gap — 1× in this paper · explained in 2 episodes
• Quantile Score — 1× in this paper
• Temporal Reasoning — 1× in this paper · explained in 3 episodes
• Training Objective — 1× in this paper · explained in 3 episodes
• Uncertainty Quantification — 1× in this paper · explained in 9 episodes

Sources

• Embedding Entities and Relations for Learning and Inference in Knowledge Bases
• Self-Attentive Hawkes Processes

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