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

423 papers, page 6 of 9

251. ICML 2024Ambiguity-Aware Abductive Learning
252. ICML 2024An Empirical Study of Realized GNN Expressiveness
253. ICML 2024Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification
254. ICML 2024Bayesian Program Learning by Decompiling Amortized Knowledge
255. ICML 2024Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS
256. ICML 2024Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
257. ICML 2024CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback
258. ICML 2024Class-Imbalanced Graph Learning without Class Rebalancing
259. ICML 2024Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models
260. ICML 2024Community-Invariant Graph Contrastive Learning
261. ICML 2024Comparing Graph Transformers via Positional Encodings
262. ICML 2024Convergence Guarantees for the DeepWalk Embedding on Block Models
263. ICML 2024DetKDS: Knowledge Distillation Search for Object Detectors
264. ICML 2024Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View
265. ICML 2024DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
266. ICML 2024Differentially Private Decentralized Learning with Random Walks
267. ICML 2024Diffusion Models Encode the Intrinsic Dimension of Data Manifolds
268. ICML 2024Do Topological Characteristics Help in Knowledge Distillation?
269. ICML 2024DUPLEX: Dual GAT for Complex Embedding of Directed Graphs
270. ICML 2024Dynamic Metric Embedding into lp Space
271. ICML 2024Dynamic Spectral Clustering with Provable Approximation Guarantee
272. ICML 2024Efficient Contextual Bandits with Uninformed Feedback Graphs
273. ICML 2024Efficient Contrastive Learning for Fast and Accurate Inference on Graphs
274. ICML 2024Empowering Graph Invariance Learning with Deep Spurious Infomax
275. ICML 2024Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation
276. ICML 2024EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
277. ICML 2024Exploring Correlations of Self-Supervised Tasks for Graphs
278. ICML 2024Faster Streaming and Scalable Algorithms for Finding Directed Dense Subgraphs in Large Graphs
279. ICML 2024Federated Continual Learning via Prompt-based Dual Knowledge Transfer
280. ICML 2024FreeBind: Free Lunch in Unified Multimodal Space via Knowledge Fusion
281. ICML 2024From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble
282. ICML 2024Gaussian Processes on Cellular Complexes
283. ICML 2024Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization
284. ICML 2024Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks
285. ICML 2024GPTSwarm: Language Agents as Optimizable Graphs
286. ICML 2024Graph As Point Set
287. ICML 2024Graph Automorphism Group Equivariant Neural Networks
288. ICML 2024Graph Mixup on Approximate Gromov–Wasserstein Geodesics
289. ICML 2024Graph Neural Network Explanations are Fragile
290. ICML 2024Graph Neural Networks Use Graphs When They Shouldn't
291. ICML 2024Graph Neural Networks with a Distribution of Parametrized Graphs
292. ICML 2024Graph-enhanced Large Language Models in Asynchronous Plan Reasoning
293. ICML 2024Graph-Triggered Rising Bandits
294. ICML 2024How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing
295. ICML 2024Hypergraph-enhanced Dual Semi-supervised Graph Classification
296. ICML 2024Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning
297. ICML 2024Incorporating Information into Shapley Values: Reweighting via a Maximum Entropy Approach
298. ICML 2024Incorporating probabilistic domain knowledge into deep multiple instance learning
299. ICML 2024Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
300. ICML 2024KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning

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.