Knowledge Graphs papers, 2023–2026

Key findings

• Knowledge Graphs went from 287 papers in 2023 to 536 in 2026, roughly 1.9x in three years.
• ICLR publishes the most Knowledge Graphs work: 571 papers from 2023 to 2026, 33% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 17 in 2023 to 93 in 2026.
• Among the 5 topics under Graph and Structured Data, it ranks #2 by 2026 paper count; the fastest grower in the group, Time Series, is up 3.2x versus 1.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Aligning LLMs with Biomedical Knowledge using Balanced Fine-Tuning
• ICML 2026Belief Propagation Converges to Gaussian Distributions in Sparsely-Connected Factor Graphs
• ICLR 2026$\ell_1$ Latent Distance based Continuous-time Graph Representation
• CVPR 2026A Unified Framework for Knowledge Transfer in Bidirectional Model Scaling
• NeurIPS 2025A CLT for Polynomial GNNs on Community-Based Graphs
• ICML 2025A Selective Learning Method for Temporal Graph Continual Learning
• ICLR 2025$R^2$-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning
• CVPR 2025A Hubness Perspective on Representation Learning for Graph-Based Multi-View Clustering
• NeurIPS 2024Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models
• ICML 2024Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS
• ICLR 2024A Good Learner can Teach Better: Teacher-Student Collaborative Knowledge Distillation
• CVPR 2024De-confounded Data-free Knowledge Distillation for Handling Distribution Shifts
• NeurIPS 2023A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking
• ICML 2023A Generalization of ViT/MLP-Mixer to Graphs
• ICLR 2023A Differential Geometric View and Explainability of GNN on Evolving Graphs
• CVPR 2023A Unified Knowledge Distillation Framework for Deep Directed Graphical Models
• NeurIPS 2026AT-SKM-Net: An Accelerated Trainable Sampling Kaczmarz-Motzkin Framework for Linear Hard-Constraint Feasibility on Dynamic Graphs
• ICML 2026Cross-Modal Knowledge Distillation without Paired Data: Theoretical Foundation and Algorithm
• ICLR 2026A Graph Meta-Network for Learning on Kolmogorov–Arnold Networks
• CVPR 2026Distilling Balanced Knowledge from a Biased Teacher

All Knowledge Graphs papers

103 papers, page 2 of 3

51. ICML 2024Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
52. ICML 2024KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning
53. ICML 2024Knowledge Distillation with Auxiliary Variable
54. ICML 2024Knowledge Graphs Can be Learned with Just Intersection Features
55. ICML 2024Knowledge-aware Reinforced Language Models for Protein Directed Evolution
56. ICML 2024Layerwise Change of Knowledge in Neural Networks
57. ICML 2024Learning in Deep Factor Graphs with Gaussian Belief Propagation
58. ICML 2024Learning Modality Knowledge Alignment for Cross-Modality Transfer
59. ICML 2024Learning to Explore in POMDPs with Informational Rewards
60. ICML 2024Less is More: on the Over-Globalizing Problem in Graph Transformers
61. ICML 2024LLaGA: Large Language and Graph Assistant
62. ICML 2024Long Range Propagation on Continuous-Time Dynamic Graphs
63. ICML 2024MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models
64. ICML 2024Mitigating Label Noise on Graphs via Topological Sample Selection
65. ICML 2024Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs
66. ICML 2024Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching
67. ICML 2024Neighboring Perturbations of Knowledge Editing on Large Language Models
68. ICML 2024Neural Tangent Kernels Motivate Cross-Covariance Graphs in Neural Networks
69. ICML 2024Neuro-Visualizer: A Novel Auto-Encoder-Based Loss Landscape Visualization Method With an Application in Knowledge-Guided Machine Learning
70. ICML 2024OAK: Enriching Document Representations using Auxiliary Knowledge for Extreme Classification
71. ICML 2024On dimensionality of feature vectors in MPNNs
72. ICML 2024On the Expressive Power of Spectral Invariant Graph Neural Networks
73. ICML 2024On the Feasibility of Single-Pass Full-Capacity Learning in Linear Threshold Neurons with Binary Input Vectors
74. ICML 2024Optimal Batched Linear Bandits
75. ICML 2024PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
76. ICML 2024PANDA: Expanded Width-Aware Message Passing Beyond Rewiring
77. ICML 2024Physics of Language Models: Part 3.1, Knowledge Storage and Extraction
78. ICML 2024PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
79. ICML 2024Position: Why We Must Rethink Empirical Research in Machine Learning
80. ICML 2024Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
81. ICML 2024QBMK: Quantum-based Matching Kernels for Un-attributed Graphs
82. ICML 2024Rethinking Momentum Knowledge Distillation in Online Continual Learning
83. ICML 2024Revisit the Essence of Distilling Knowledge through Calibration
84. ICML 2024Robust Graph Matching when Nodes are Corrupt
85. ICML 2024S3GCL: Spectral, Swift, Spatial Graph Contrastive Learning
86. ICML 2024Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency
87. ICML 2024Semantically-correlated memories in a dense associative model
88. ICML 2024SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
89. ICML 2024SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States
90. ICML 2024Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
91. ICML 2024SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter
92. ICML 2024Stochastic Bandits with ReLU Neural Networks
93. ICML 2024Sub-token ViT Embedding via Stochastic Resonance Transformers
94. ICML 2024Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
95. ICML 2024Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning
96. ICML 2024The Expressive Power of Path-Based Graph Neural Networks
97. ICML 2024Transferring Knowledge From Large Foundation Models to Small Downstream Models
98. ICML 2024Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness
99. ICML 2024Uncertainty for Active Learning on Graphs
100. ICML 2024Understanding Finetuning for Factual Knowledge Extraction

FAQ

How many Knowledge Graphs papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,715 in total: 287 in 2023, 426 in 2024, 466 in 2025, 536 in 2026.

How many Knowledge Graphs papers are at NeurIPS 2026?

NeurIPS 2026 has 133 Knowledge Graphs papers, versus 154 the year before.

How many Knowledge Graphs papers are at ICLR 2026?

ICLR 2026 has 201 Knowledge Graphs papers, versus 172 the year before.

How many Knowledge Graphs papers are at ICML 2026?

ICML 2026 has 149 Knowledge Graphs papers, versus 99 the year before.

How many Knowledge Graphs papers are at CVPR 2026?

CVPR 2026 has 53 Knowledge Graphs papers, versus 41 the year before.

Which conference publishes the most Knowledge Graphs papers?

ICLR, with 571 papers from 2023 to 2026.