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

466 papers, page 5 of 10

201. ICLR 2025Towards Automated Knowledge Integration From Human-Interpretable Representations
202. ICLR 2025Towards Bridging Generalization and Expressivity of Graph Neural Networks
203. ICLR 2025Towards Continuous Reuse of Graph Models via Holistic Memory Diversification
204. ICLR 2025Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming
205. ICLR 2025Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy Hessians
206. ICLR 2025Towards Synergistic Path-based Explanations for Knowledge Graph Completion: Exploration and Evaluation
207. ICLR 2025Training-Free Message Passing for Learning on Hypergraphs
208. ICLR 2025Uncovering Overfitting in Large Language Model Editing
209. ICLR 2025Understanding Virtual Nodes: Oversquashing and Node Heterogeneity
210. ICLR 2025Unsupervised Multiple Kernel Learning for Graphs via Ordinality Preservation
211. ICLR 2025Valid Conformal Prediction for Dynamic GNNs
212. ICLR 2025What Are Good Positional Encodings for Directed Graphs?
213. ICLR 2025When Graph Neural Networks Meet Dynamic Mode Decomposition
214. ICML 2025A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
215. ICML 2025A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Features
216. ICML 2025A Selective Learning Method for Temporal Graph Continual Learning
217. ICML 2025ABKD: Pursuing a Proper Allocation of the Probability Mass in Knowledge Distillation via $\alpha$-$\beta$-Divergence
218. ICML 2025Adaptive Localization of Knowledge Negation for Continual LLM Unlearning
219. ICML 2025Algorithms and Hardness for Active Learning on Graphs
220. ICML 2025An Improved Clique-Picking Algorithm for Counting Markov Equivalent DAGs via Super Cliques Transfer
221. ICML 2025AnyEdit: Edit Any Knowledge Encoded in Language Models
222. ICML 2025Best of Both Worlds: Advantages of Hybrid Graph Sequence Models
223. ICML 2025Beyond Message Passing: Neural Graph Pattern Machine
224. ICML 2025Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs
225. ICML 2025Bridging Layout and RTL: Knowledge Distillation based Timing Prediction
226. ICML 2025CoDy: Counterfactual Explainers for Dynamic Graphs
227. ICML 2025Commute Graph Neural Networks
228. ICML 2025Componential Prompt-Knowledge Alignment for Domain Incremental Learning
229. ICML 2025Core Knowledge Deficits in Multi-Modal Language Models
230. ICML 2025Cross-City Latent Space Alignment for Consistency Region Embedding
231. ICML 2025CSG-ODE: ControlSynth Graph ODE For Modeling Complex Evolution of Dynamic Graphs
232. ICML 2025De-coupled NeuroGF for Shortest Path Distance Approximations on Large Terrain Graphs
233. ICML 2025Directed Graph Grammars for Sequence-based Learning
234. ICML 2025Discovering Latent Causal Graphs from Spatiotemporal Data
235. ICML 2025Distilling the Knowledge in Data Pruning
236. ICML 2025Does Graph Prompt Work? A Data Operation Perspective with Theoretical Analysis
237. ICML 2025Dynamic Similarity Graph Construction with Kernel Density Estimation
238. ICML 2025Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment
239. ICML 2025Enhancing Foundation Models with Federated Domain Knowledge Infusion
240. ICML 2025Enhancing Graph Contrastive Learning for Protein Graphs from Perspective of Invariance
241. ICML 2025Enhancing Logits Distillation with Plug&Play Kendall's $\tau$ Ranking Loss
242. ICML 2025From Complex to Atomic: Enhancing Augmented Generation via Knowledge-Aware Dual Rewriting and Reasoning
243. ICML 2025From Theory to Practice: Rethinking Green and Martin Kernels for Unleashing Graph Transformers
244. ICML 2025Fully Dynamic Embedding into $\ell_p$ Spaces
245. ICML 2025GCAL: Adapting Graph Models to Evolving Domain Shifts
246. ICML 2025Generalization Principles for Inference over Text-Attributed Graphs with Large Language Models
247. ICML 2025GHOST: Generalizable One-Shot Federated Graph Learning with Proxy-Based Topology Knowledge Retention
248. ICML 2025Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models
249. ICML 2025Graph Minimum Factor Distance and Its Application to Large-Scale Graph Data Clustering
250. ICML 2025Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models

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.