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

426 papers, page 3 of 9

101. ICLR 2024Knowledge Fusion of Large Language Models
102. ICLR 2024KoLA: Carefully Benchmarking World Knowledge of Large Language Models
103. ICLR 2024KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement
104. ICLR 2024Label-free Node Classification on Graphs with Large Language Models (LLMs)
105. ICLR 2024Latent 3D Graph Diffusion
106. ICLR 2024Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network
107. ICLR 2024Learning From Simplicial Data Based on Random Walks and 1D Convolutions
108. ICLR 2024Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG
109. ICLR 2024Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs
110. ICLR 2024Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
111. ICLR 2024LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference
112. ICLR 2024Local Graph Clustering with Noisy Labels
113. ICLR 2024Locality-Aware Graph Rewiring in GNNs
114. ICLR 2024Manifold Diffusion Fields
115. ICLR 2024MiniLLM: Knowledge Distillation of Large Language Models
116. ICLR 2024Mirage: Model-agnostic Graph Distillation for Graph Classification
117. ICLR 2024Mitigating Emergent Robustness Degradation while Scaling Graph Learning
118. ICLR 2024Mixture of Weak and Strong Experts on Graphs
119. ICLR 2024MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy
120. ICLR 2024NetInfoF Framework: Measuring and Exploiting Network Usable Information
121. ICLR 2024Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel
122. ICLR 2024Neural Common Neighbor with Completion for Link Prediction
123. ICLR 2024Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries
124. ICLR 2024On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods
125. ICLR 2024On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters
126. ICLR 2024On the Stability of Expressive Positional Encodings for Graphs
127. ICLR 2024One For All: Towards Training One Graph Model For All Classification Tasks
128. ICLR 2024Orbit-Equivariant Graph Neural Networks
129. ICLR 2024PAE: Reinforcement Learning from External Knowledge for Efficient Exploration
130. ICLR 2024Partitioning Message Passing for Graph Fraud Detection
131. ICLR 2024Predictive, scalable and interpretable knowledge tracing on structured domains
132. ICLR 2024PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
133. ICLR 2024Probabilistically Rewired Message-Passing Neural Networks
134. ICLR 2024Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks
135. ICLR 2024Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
136. ICLR 2024Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning
137. ICLR 2024Repelling Random Walks
138. ICLR 2024Rethinking and Extending the Probabilistic Inference Capacity of GNNs
139. ICLR 2024Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors
140. ICLR 2024Rethinking Label Poisoning for GNNs: Pitfalls and Attacks
141. ICLR 2024Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
142. ICLR 2024Revisit and Outstrip Entity Alignment: A Perspective of Generative Models
143. ICLR 2024Revisiting Link Prediction: a data perspective
144. ICLR 2024Robust Angular Synchronization via Directed Graph Neural Networks
145. ICLR 2024SaNN: Simple Yet Powerful Simplicial-aware Neural Networks
146. ICLR 2024Scalable and Effective Implicit Graph Neural Networks on Large Graphs
147. ICLR 2024Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective
148. ICLR 2024SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
149. ICLR 2024Simplicial Representation Learning with Neural $k$-Forms
150. ICLR 2024Structural Fairness-aware Active Learning for Graph Neural Networks

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.