NeurIPS 2025 accepted papers on Graph learning
202 of the 5,812 papers accepted at NeurIPS 2025 (3.5%) are on Graph learning, compared with 4.0% at NeurIPS 2024. They fall into 4 topics.
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Topics and papers
Graph self-supervised learning · 72 papers
- Self-Supervised Learning of Graph Representations for Network Intrusion Detection (4 citations)
- One Prompt Fits All: Universal Graph Adaptation for Pretrained Models (2 citations)
- Adversarial Graph Fusion for Incomplete Multi-view Semi-supervised Learning with Tensorial Imputation (1 citation)
- Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features (1 citation)
- Conditional Diffusion Anomaly Modeling on Graphs (1 citation)
- DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platform (1 citation)
- Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models (1 citation)
- Graph Data Selection for Domain Adaptation: A Model-Free Approach (1 citation)
- Graph Few-Shot Learning via Adaptive Spectrum Experts and Cross-Set Distribution Calibration (1 citation)
- Graph-Theoretic Insights into Bayesian Personalized Ranking for Recommendation (1 citation)
- GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning (1 citation)
- IA-GGAD: Zero-shot Generalist Graph Anomaly Detection via Invariant and Affinity Learning (1 citation)
and 60 more in the interactive map.
GNN architectures · 69 papers
- Less but More: Linear Adaptive Graph Learning Empowering Spatiotemporal Forecasting (5 citations)
- Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models (2 citations)
- On Logic-based Self-Explainable Graph Neural Networks (2 citations)
- Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks (2 citations)
- Diffusion-Based Hierarchical Graph Neural Networks for Simulating Nonlinear Solid Mechanics (1 citation)
- Diffusion-Guided Graph Data Augmentation (1 citation)
- Generative Graph Pattern Machine (1 citation)
- GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data (1 citation)
- Making Classic GNNs Strong Baselines Across Varying Homophily: A Smoothness–Generalization Perspective (1 citation)
- Memorization in Graph Neural Networks (1 citation)
- On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning (1 citation)
- OpenGU: A Comprehensive Benchmark for Graph Unlearning (1 citation)
and 57 more in the interactive map.
Knowledge and temporal graphs · 34 papers
- HyperGraphRAG: Retrieval-Augmented Generation via Hypergraph-Structured Knowledge Representation (9 citations)
- KGGen: Extracting Knowledge Graphs from Plain Text with Language Models (9 citations)
- GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation (8 citations)
- STRAP: Spatio-Temporal Pattern Retrieval for Out-of-Distribution Generalization (4 citations)
- Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs (3 citations)
- DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs (2 citations)
- Unifying Text Semantics and Graph Structures for Temporal Text-attributed Graphs with Large Language Models (2 citations)
- Defining and Discovering Hyper-meta-paths for Heterogeneous Hypergraphs (1 citation)
- DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning with Dual-Pathway Global-Local Fusion (1 citation)
- Make Information Diffusion Explainable: LLM-based Causal Framework for Diffusion Prediction (1 citation)
- Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting (1 citation)
- RAG4GFM: Bridging Knowledge Gaps in Graph Foundation Models through Graph Retrieval Augmented Generation (1 citation)
and 22 more in the interactive map.
Graph algorithms and clustering · 27 papers
- Adjusted Count Quantification Learning on Graphs (1 citation)
- EverybodyDance: Bipartite Graph–Based Identity Correspondence for Multi-Character Animation (1 citation)
- A Few Moments Please: Scalable Graphon Learning via Moment Matching
- A Generalized Binary Tree Mechanism for Private Approximation of All-Pair Shortest Distances
- Adaptive Frontier Exploration on Graphs with Applications to Network-Based Disease Testing
- An Efficient Orlicz-Sobolev Approach for Transporting Unbalanced Measures on a Graph
- Causal-R: A Causal-Reasoning Geometry Problem Solver for Optimized Solution Exploration
- DGCBench: A Deep Graph Clustering Benchmark
- Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search
- Dynamic Configuration for Cutting Plane Separators via Reinforcement Learning on Incremental Graph
- Graph Alignment via Birkhoff Relaxation
- Graph Neural Network Based Action Ranking for Planning
and 15 more in the interactive map.