Knowledge and temporal graphs: research map
974 accepted papers on Knowledge and temporal graphs in Graph learning, from ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026), grouped into 3 clusters and 12 approaches. The busiest year so far is 2026.
Within Graph learning, its share shrank from 20.3% in 2023–24 to 18.0% in 2025–26 (258 → 283 papers at ICML, NeurIPS, CVPR and AAAI, the venues with data for all four years).
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Approaches and key papers
scene · image · visual · 413 papers
Approaches in this cluster:
- Graph reasoning for visual recognition (96 papers)
Model relations among regions, actors, and skeleton joints using graph networks. - Graph-based dialog systems (94 papers)
Use graph structures for dialog reasoning and language model context. - Heterogeneous graph learning (66 papers)
Learn from and explain heterogeneous graphs with transfer and relational methods. - Social and behavior graphs (87 papers)
Model social interactions with graphs for trajectory and behavior prediction. - Scene graph generation (70 papers)
Generate scene graphs with unbiased relation learning and transformers.
Most cited and most cited since 2024:
- Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition (CVPR 2019 · 2,091 citations)
- Actional-Structural Graph Convolutional Networks for Skeleton-Based Action Recognition (CVPR 2019 · 1,272 citations)
- BlockGCN: Redefine Topology Awareness for Skeleton-Based Action Recognition (CVPR 2024 · 176 citations)
- LGMRec: Local and Global Graph Learning for Multimodal Recommendation (AAAI 2024 · 146 citations)
knowledge graph · entities · kg · 300 papers
Approaches in this cluster:
- Knowledge graph embeddings (110 papers)
Embed entities and relations with geometric transformations for link prediction. - Temporal knowledge graph reasoning (84 papers)
Forecast and reason over time-evolving knowledge graphs using rules and sequence models. - Logical query answering and rule reasoning (68 papers)
Answer logical queries and induce rules with neuro-symbolic path-based reasoning. - Inductive knowledge graph completion (38 papers)
Complete knowledge graphs for unseen entities using relational semantics and GNNs.
Most cited and most cited since 2024:
- RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space (ICLR 2019 · 756 citations)
- Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning (ICLR 2018 · 398 citations)
- MKG-FENN: A Multimodal Knowledge Graph Fused End-to-End Neural Network for Accurate Drug–Drug Interaction Prediction (AAAI 2024 · 41 citations)
- MINES: Message Intercommunication for Inductive Relation Reasoning over Neighbor-Enhanced Subgraphs (AAAI 2024 · 34 citations)
dynamic · temporal graph · spatio temporal · 261 papers
Approaches in this cluster:
- Continuous-time dynamic graph learning (132 papers)
Model link prediction on continuous-time dynamic graphs and benchmark temporal graph learning. - Temporal graph neural architectures (69 papers)
Design state-space, motif-based, and spiking architectures for dynamic graphs. - Spatio-temporal graph traffic forecasting (60 papers)
Forecast traffic with spatio-temporal graph neural networks.
Most cited and most cited since 2024:
- Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition (CVPR 2020 · 1,219 citations)
- Structural-RNN: Deep Learning on Spatio-Temporal Graphs (CVPR 2016 · 1,151 citations)
- Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting (AAAI 2024 · 129 citations)
- Temporal Graph Contrastive Learning for Sequential Recommendation (AAAI 2024 · 62 citations)
Related topics in Graph learning
- Graph algorithms and clustering (817)
- GNN architectures (1,471)
- Graph self-supervised learning (1,274)