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 7 of 10

301. ICML 2025TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation
302. ICML 2025TMetaNet: Topological Meta-Learning Framework for Dynamic Link Prediction
303. ICML 2025TopInG: Topologically Interpretable Graph Learning via Persistent Rationale Filtration
304. ICML 2025Toward Data-centric Directed Graph Learning: An Entropy-driven Approach
305. ICML 2025Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees
306. ICML 2025Towards Understanding Parametric Generalized Category Discovery on Graphs
307. ICML 2025Trusted Multi-View Classification with Expert Knowledge Constraints
308. ICML 2025Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
309. ICML 2025Unifying Knowledge from Diverse Datasets to Enhance Spatial-Temporal Modeling: A Granularity-Adaptive Geographical Embedding Approach
310. ICML 2025Weisfeiler and Leman Go Gambling: Why Expressive Lottery Tickets Win
311. ICML 2025What Makes a Good Feedforward Computational Graph?
312. ICML 2025When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need
313. NeurIPS 2025$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
314. NeurIPS 2025A CLT for Polynomial GNNs on Community-Based Graphs
315. NeurIPS 2025A Pre-training Framework for Relational Data with Information-theoretic Principles
316. NeurIPS 2025A Signed Graph Approach to Understanding and Mitigating Oversmoothing
317. NeurIPS 2025A Token is Worth over 1,000 Tokens: Efficient Knowledge Distillation through Low-Rank Clone
318. NeurIPS 2025AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders
319. NeurIPS 2025Adjusted Count Quantification Learning on Graphs
320. NeurIPS 2025Angular Constraint Embedding via SpherePair Loss for Constrained Clustering
321. NeurIPS 2025Black-Box Membership Inference Attack for LVLMs via Prior Knowledge-Calibrated Memory Probing
322. NeurIPS 2025C$^2$Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning
323. NeurIPS 2025Can Knowledge-Graph-based Retrieval Augmented Generation Really Retrieve What You Need?
324. NeurIPS 2025Characterization and Learning of Causal Graphs from Hard Interventions
325. NeurIPS 2025Co-Regularization Enhances Knowledge Transfer in High Dimensions
326. NeurIPS 2025Codifying Character Logic in Role-Playing
327. NeurIPS 2025Conditional Diffusion Anomaly Modeling on Graphs
328. NeurIPS 2025Conflict-Aware Knowledge Editing in the Wild: Semantic-Augmented Graph Representation for Unstructured Text
329. NeurIPS 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
330. NeurIPS 2025Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models
331. NeurIPS 2025Curriculum Abductive Learning
332. NeurIPS 2025Data Mixing Can Induce Phase Transitions in Knowledge Acquisition
333. NeurIPS 2025DCA: Graph-Guided Deep Embedding Clustering for Brain Atlases
334. NeurIPS 2025Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models
335. NeurIPS 2025DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation Trainer
336. NeurIPS 2025Defining and Discovering Hyper-meta-paths for Heterogeneous Hypergraphs
337. NeurIPS 2025Deliberation on Priors: Trustworthy Reasoning of Large Language Models on Knowledge Graphs
338. NeurIPS 2025Democratizing Clinical Risk Prediction with Cross-Cohort Cross-Modal Knowledge Transfer
339. NeurIPS 2025Dependency Matters: Enhancing LLM Reasoning with Explicit Knowledge Grounding
340. NeurIPS 2025Diagnosing and Addressing Pitfalls in KG-RAG Datasets: Toward More Reliable Benchmarking
341. NeurIPS 2025Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search
342. NeurIPS 2025Distribution Learning Meets Graph Structure Sampling
343. NeurIPS 2025DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning
344. NeurIPS 2025Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
345. NeurIPS 2025DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning with Dual-Pathway Global-Local Fusion
346. NeurIPS 2025DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs
347. NeurIPS 2025Dynamic Bundling with Large Language Models for Zero-Shot Inference on Text-Attributed Graphs
348. NeurIPS 2025Edit Less, Achieve More: Dynamic Sparse Neuron Masking for Lifelong Knowledge Editing in LLMs
349. NeurIPS 2025Efficient Knowledge Transfer in Federated Recommendation for Joint Venture Ecosystem
350. NeurIPS 2025Efficient Verified Unlearning For Distillation

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.