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

287 papers, page 5 of 6

201. ICML 2023Taming graph kernels with random features
202. ICML 2023TIDE: Time Derivative Diffusion for Deep Learning on Graphs
203. ICML 2023Tight and fast generalization error bound of graph embedding in metric space
204. ICML 2023Total Variation Graph Neural Networks
205. ICML 2023Towards Robust Graph Incremental Learning on Evolving Graphs
206. ICML 2023Towards Understanding and Reducing Graph Structural Noise for GNNs
207. ICML 2023Transformers Meet Directed Graphs
208. ICML 2023Weighted Flow Diffusion for Local Graph Clustering with Node Attributes: an Algorithm and Statistical Guarantees
209. ICML 2023What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings
210. ICML 2023Who Needs to Know? Minimal Knowledge for Optimal Coordination
211. ICML 2023WL meet VC
212. NeurIPS 2023A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking
213. NeurIPS 2023A Fractional Graph Laplacian Approach to Oversmoothing
214. NeurIPS 2023A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs
215. NeurIPS 2023A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs
216. NeurIPS 2023Accelerating Molecular Graph Neural Networks via Knowledge Distillation
217. NeurIPS 2023Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs
218. NeurIPS 2023Adapting Neural Link Predictors for Data-Efficient Complex Query Answering
219. NeurIPS 2023Bayesian Optimisation of Functions on Graphs
220. NeurIPS 2023Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks
221. NeurIPS 2023Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs
222. NeurIPS 2023Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond
223. NeurIPS 2023Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints
224. NeurIPS 2023Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards
225. NeurIPS 2023Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
226. NeurIPS 2023Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs
227. NeurIPS 2023Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization
228. NeurIPS 2023Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork
229. NeurIPS 2023Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization
230. NeurIPS 2023Evaluating Self-Supervised Learning for Molecular Graph Embeddings
231. NeurIPS 2023Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing
232. NeurIPS 2023Expressivity-Preserving GNN Simulation
233. NeurIPS 2023Fast Approximation of Similarity Graphs with Kernel Density Estimation
234. NeurIPS 2023Fine-grained Expressivity of Graph Neural Networks
235. NeurIPS 2023Fitting trees to $\ell_1$-hyperbolic distances
236. NeurIPS 2023Fragment-based Pretraining and Finetuning on Molecular Graphs
237. NeurIPS 2023From Trainable Negative Depth to Edge Heterophily in Graphs
238. NeurIPS 2023Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge
239. NeurIPS 2023Geometric Analysis of Matrix Sensing over Graphs
240. NeurIPS 2023GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels
241. NeurIPS 2023Grounding Neural Inference with Satisfiability Modulo Theories
242. NeurIPS 2023HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding
243. NeurIPS 2023How to Turn Your Knowledge Graph Embeddings into Generative Models
244. NeurIPS 2023Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network
245. NeurIPS 2023Improving the Knowledge Gradient Algorithm
246. NeurIPS 2023Joint Feature and Differentiable $ k $-NN Graph Learning using Dirichlet Energy
247. NeurIPS 2023KD-Zero: Evolving Knowledge Distiller for Any Teacher-Student Pairs
248. NeurIPS 2023Kernelized Cumulants: Beyond Kernel Mean Embeddings
249. NeurIPS 2023Knowledge Diffusion for Distillation
250. NeurIPS 2023Knowledge Distillation for High Dimensional Search Index

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.