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

1,715 papers, page 33 of 35

1601. ICML 2023Knowledge Hypergraph Embedding Meets Relational Algebra
1602. ICML 2023Large Language Models Struggle to Learn Long-Tail Knowledge
1603. ICML 2023LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
1604. ICML 2023Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs
1605. ICML 2023Linear optimal partial transport embedding
1606. ICML 2023Local Vertex Colouring Graph Neural Networks
1607. ICML 2023Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single
1608. ICML 2023MetricGAN-OKD: Multi-Metric Optimization of MetricGAN via Online Knowledge Distillation for Speech Enhancement
1609. ICML 2023Nearly-Optimal Hierarchical Clustering for Well-Clustered Graphs
1610. ICML 2023Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal
1611. ICML 2023On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs
1612. ICML 2023On the Impact of Knowledge Distillation for Model Interpretability
1613. ICML 2023One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding
1614. ICML 2023Online Learning with Feedback Graphs: The True Shape of Regret
1615. ICML 2023Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs
1616. ICML 2023Quantum 3D Graph Learning with Applications to Molecule Embedding
1617. ICML 2023Regression with Label Permutation in Generalized Linear Model
1618. ICML 2023Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching
1619. ICML 2023Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge
1620. ICML 2023Revisiting Data-Free Knowledge Distillation with Poisoned Teachers
1621. ICML 2023RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agents
1622. ICML 2023SeedGNN: Graph Neural Network for Supervised Seeded Graph Matching
1623. ICML 2023Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains
1624. ICML 2023Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model
1625. ICML 2023SlotGAT: Slot-based Message Passing for Heterogeneous Graphs
1626. ICML 2023Speeding Up Bellman Ford via Minimum Violation Permutations
1627. ICML 2023Structure Learning of Latent Factors via Clique Search on Correlation Thresholded Graphs
1628. ICML 2023Structured Cooperative Learning with Graphical Model Priors
1629. ICML 2023Taming graph kernels with random features
1630. ICML 2023TIDE: Time Derivative Diffusion for Deep Learning on Graphs
1631. ICML 2023Tight and fast generalization error bound of graph embedding in metric space
1632. ICML 2023Total Variation Graph Neural Networks
1633. ICML 2023Towards Robust Graph Incremental Learning on Evolving Graphs
1634. ICML 2023Towards Understanding and Reducing Graph Structural Noise for GNNs
1635. ICML 2023Transformers Meet Directed Graphs
1636. ICML 2023Weighted Flow Diffusion for Local Graph Clustering with Node Attributes: an Algorithm and Statistical Guarantees
1637. ICML 2023What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings
1638. ICML 2023Who Needs to Know? Minimal Knowledge for Optimal Coordination
1639. ICML 2023WL meet VC
1640. NeurIPS 2023A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking
1641. NeurIPS 2023A Fractional Graph Laplacian Approach to Oversmoothing
1642. NeurIPS 2023A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs
1643. NeurIPS 2023A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs
1644. NeurIPS 2023Accelerating Molecular Graph Neural Networks via Knowledge Distillation
1645. NeurIPS 2023Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs
1646. NeurIPS 2023Adapting Neural Link Predictors for Data-Efficient Complex Query Answering
1647. NeurIPS 2023Bayesian Optimisation of Functions on Graphs
1648. NeurIPS 2023Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks
1649. NeurIPS 2023Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs
1650. NeurIPS 2023Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond

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.