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

516 papers, page 3 of 11

101. NeurIPS 2026Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning
102. NeurIPS 2026RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with LLMs
103. NeurIPS 2026Robust and Hard-to-Remove GNN Watermarking via Topological Invariant Perception
104. NeurIPS 2026S3Former: Sequential, Structural, and Statistical Fusion for Continuous-Time Dynamic Graphs
105. NeurIPS 2026SGNNBench: A Holistic Evaluation of Spiking Graph Neural Networks on Large-scale Graphs
106. NeurIPS 2026Similarity-Constrained Reweighting for Complex Query Answering on Knowledge Graphs
107. NeurIPS 2026Simple yet Effective Semi-supervised Knowledge Distillation from Vision-Language Models via Dual-Head Optimization
108. NeurIPS 2026SKIM: Pruning Large Language Model Agents via Selective Knowledge Informed Masking
109. NeurIPS 2026Spatial Representation Distillation and Knowledge Routing for Vision-Language-Action Models
110. NeurIPS 2026Speculative Self-Distillation enables Efficient Knowledge Internalization
111. NeurIPS 2026Stabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVR
112. NeurIPS 2026The Fractured Interlingua: Geometric Bottlenecks in Cross-Lingual Knowledge Editing
113. NeurIPS 2026The Geometry of Forgetting: Temporal Knowledge Drift as an Independent Axis in LLM Representations
114. NeurIPS 2026The Graph Concept Bottleneck: Decoding Combinatorial Reasoning in GNNs for Interpretability
115. NeurIPS 2026The Illusion of Forgetting: Rank Leakage in Knowledge Editing and Its Mitigation
116. NeurIPS 2026The Override Gap: A Magnitude Account of Knowledge Conflict Failure in Hypernetwork-Based Instant LLM Adaptation
117. NeurIPS 2026The Query Complexity of Local Search in Rounds on General Graphs
118. NeurIPS 2026They Can See It but not Say It: Iterative Self Knowledge Re-expression in Visual Reasoning Relative Pose Identification
119. NeurIPS 2026Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning
120. NeurIPS 2026Towards Generalist Graph-Level Anomaly Detection
121. NeurIPS 2026Towards Precise Knowledge Distillation for Large Language Models via Knowledge Probing
122. NeurIPS 2026Transformers Provably Learn Graph Search: Training Dynamics and the Exponential Power of Depth
123. NeurIPS 2026Traversal-Invariant Positional Encoding for Serialized Graphs
124. NeurIPS 2026Tree Search With Predictions
125. NeurIPS 2026UFO: A Unified Flow-Oriented Framework for Robust Continual Graph Learning
126. NeurIPS 2026Uncovering Semantic Hierarchies in Text-Attributed Graphs via Variational EM-based LLM–GNN Synergy
127. NeurIPS 2026VOID: Backdoor Injection through Knowledge Vacuity in Federated Unlearning
128. NeurIPS 2026Weisfeiler and Leman Follow the Arrow of Time: Expressive Power of Message Passing in Temporal Event Graphs
129. NeurIPS 2026Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them
130. NeurIPS 2026When Does Fine-Tuning Extract Stored Knowledge? A Relation-Covering Theory for One-Layer Transformers
131. NeurIPS 2026xVGAE: A Hierarchical Variational Graph Autoencoder for Exchangeable Graphs
132. NeurIPS 2026You Don’t Need Aligned Representations: Knowledge Distillation via Random Prototype Spaces
133. NeurIPS 2026Your Embedding Model Is SMARTer Than You Think
134. NeurIPS 2025$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
135. NeurIPS 2025A CLT for Polynomial GNNs on Community-Based Graphs
136. NeurIPS 2025A Pre-training Framework for Relational Data with Information-theoretic Principles
137. NeurIPS 2025A Signed Graph Approach to Understanding and Mitigating Oversmoothing
138. NeurIPS 2025A Token is Worth over 1,000 Tokens: Efficient Knowledge Distillation through Low-Rank Clone
139. NeurIPS 2025AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders
140. NeurIPS 2025Adjusted Count Quantification Learning on Graphs
141. NeurIPS 2025Angular Constraint Embedding via SpherePair Loss for Constrained Clustering
142. NeurIPS 2025Black-Box Membership Inference Attack for LVLMs via Prior Knowledge-Calibrated Memory Probing
143. NeurIPS 2025C$^2$Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning
144. NeurIPS 2025Can Knowledge-Graph-based Retrieval Augmented Generation Really Retrieve What You Need?
145. NeurIPS 2025Characterization and Learning of Causal Graphs from Hard Interventions
146. NeurIPS 2025Co-Regularization Enhances Knowledge Transfer in High Dimensions
147. NeurIPS 2025Codifying Character Logic in Role-Playing
148. NeurIPS 2025Conditional Diffusion Anomaly Modeling on Graphs
149. NeurIPS 2025Conflict-Aware Knowledge Editing in the Wild: Semantic-Augmented Graph Representation for Unstructured Text
150. NeurIPS 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework

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.