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 3 of 35

101. ICLR 2026Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks
102. ICLR 2026Diverse and Sparse Mixture-of-Experts for Causal Subgraph–Based Out-of-Distribution Graph Learning
103. ICLR 2026Do Large Language Models Know What They Are Capable Of?
104. ICLR 2026Do We Really Need Permutations? Impact of Width Expansion on Linear Mode Connectivity
105. ICLR 2026DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs
106. ICLR 2026DR-GGAD: Dual Residual Centering for Mitigating Anomaly Non‑Discriminativity in Generalist Graph Anomaly Detection
107. ICLR 2026Dynamic Multi-sample Mixup with Gradient Exploration for Open-set Graph Anomaly Detection
108. ICLR 2026Efficient Learning on Large Graphs using a Densifying Regularity Lemma
109. ICLR 2026Enhancing LLMs for Knowledge Base Question Answering by Chain-of-Decomposition
110. ICLR 2026EvA: Evolutionary Attacks on Graphs
111. ICLR 2026Experience-based Knowledge Correction for Robust Planning in Minecraft
112. ICLR 2026Expert Heads: Robust Evidence Identification for Large Language Models
113. ICLR 2026Explain in Your Own Words: Improving Reasoning via Token-Selective Dual Knowledge Distillation
114. ICLR 2026Explore-on-Graph: Incentivizing Autonomous Exploration of Large Language Models on Knowledge Graphs with Path-refined Reward Modeling
115. ICLR 2026Exploring Knowledge Purification in Multi-Teacher Knowledge Distillation for LLMs
116. ICLR 2026Exposing Weaknesses of Large Reasoning Models through Graph Algorithm Problems
117. ICLR 2026Expressive and Invariant Graph Learning via Canonical Tree Cover Neural Networks
118. ICLR 2026Federated Graph-Level Clustering Network with Dual Knowledge Separation
119. ICLR 2026FedMC: Federated Manifold Calibration
120. ICLR 2026Fine-tuning Done Right in Model Editing
121. ICLR 2026Flock: A Knowledge Graph Foundation Model via Learning on Random Walks
122. ICLR 2026FlowSymm: Physics–Aware, Symmetry–Preserving Graph Attention for Network Flow Completion
123. ICLR 2026Forest-Based Graph Learning for Semi-Supervised Node Classification
124. ICLR 2026Fresh in memory: Training-order recency is linearly encoded in language model activations
125. ICLR 2026FSD-CAP: Fractional Subgraph Diffusion with Class-Aware Propagation for Graph Feature Imputation
126. ICLR 2026FutureMind: Equipping Small Language Models with Strategic Thinking-Pattern Priors via Adaptive Knowledge Distillation
127. ICLR 2026G-Merging: Graph Models Merging for Parameter-Efficient Multi-Task Knowledge Consolidation
128. ICLR 2026G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge
129. ICLR 2026Gelato: Graph Edit Distance via Autoregressive Neural Combinatorial Optimization
130. ICLR 2026General search techniques without common knowledge for imperfect-information games, and application to superhuman Fog of War chess
131. ICLR 2026Generalized Spherical Neural Operators: Green’s Function Formulation
132. ICLR 2026Generating Directed Graphs with Dual Attention and Asymmetric Encoding
133. ICLR 2026Global-Recent Semantic Reasoning on Dynamic Text-Attributed Graphs with Large Language Models
134. ICLR 2026gLSTM: Mitigating Over-Squashing by Increasing Storage Capacity
135. ICLR 2026Graph homophily booster: Reimagining the role of discrete features in heterophilic graph learning
136. ICLR 2026Graph Mixing Additive Networks
137. ICLR 2026Graph Random Features for Scalable Gaussian Processes
138. ICLR 2026Graph Representational Learning: When Does More Expressivity Hurt Generalization?
139. ICLR 2026Graph Tokenization for Bridging Graphs and Transformers
140. ICLR 2026GraphOmni: A Comprehensive and Extensible Benchmark Framework for Large Language Models on Graph-theoretic Tasks
141. ICLR 2026Graphon Cross-Validation: Assessing Models on Network Data
142. ICLR 2026GraphPlanner: Graph-Based Agentic Routing for LLMs
143. ICLR 2026H$^3$GNNs: Harmonizing Heterophily and Homophily in GNNs via Self-Supervised Node Encoding
144. ICLR 2026HGNet: Scalable Foundation Model for Automated Knowledge Graph Generation from Scientific Literature
145. ICLR 2026Hourglass Persistence for Graphs, Simplices, and Cells
146. ICLR 2026HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs
147. ICLR 2026In Good GRACES: Principled Teacher Selection for Knowledge Distillation
148. ICLR 2026Inductive Reasoning for Temporal Knowledge Graphs with Emerging Entities
149. ICLR 2026Inheriting Generalizable Knowledge from LLMs to Diverse Vertical Tasks
150. ICLR 2026Interference-Isolated Elastic Weight Consolidation and Knowledge Calibration for Incremental Object Detection

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.