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

149 papers, page 3 of 3

101. ICML 2026On the Theoretical Limitations of Embedding-based Link Prediction
102. ICML 2026PACER: Acyclic Causal Discovery from Large-scale Interventional Data
103. ICML 2026PADD: Path-Aligned Decompression Distillation for Non-Router Teacher to Guide MoE Student Learning
104. ICML 2026Parametrized Power-Iteration Clustering for Directed Graphs
105. ICML 2026Plain Transformers are Surprisingly Powerful Link Predictors
106. ICML 2026PPI Candidate Ranking: Large-Scale Evaluation of a Domain Knowledge–Guided Pipeline
107. ICML 2026PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs
108. ICML 2026Provable Accuracy Collapse of Embedding-Based Representations under Dimensionality Mismatch
109. ICML 2026Quantifying Cross-Domain Knowledge Distillation in the Presence of Domain Shift
110. ICML 2026REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment
111. ICML 2026Reasoning Structure of Large Language Models
112. ICML 2026Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding
113. ICML 2026Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle
114. ICML 2026Rethinking Graph Transformers as Graph Signal Denoisers: The Role of Block-Diagonal Priors
115. ICML 2026Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence
116. ICML 2026Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing
117. ICML 2026Robust Signal Enhancement via Fractional Detail Views and Knowledge Guided Multi-view Fusion
118. ICML 2026Rotary Position Encodings for Graphs
119. ICML 2026RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation
120. ICML 2026Scalable Topology-Preserving Graph Coarsening: Concepts and Algorithms
121. ICML 2026Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration
122. ICML 2026Semi-Supervised Learning for Molecular Graphs via Ensemble Consensus
123. ICML 2026Semi-Supervised Noise Adaptation: Transferring Knowledge from Noise Domain
124. ICML 2026SG2Loc: Sequential Visual Localization on 3D Scene Graphs
125. ICML 2026Size Transferability of Graph Convolutional Networks across Sparsity: A Generalized Graphon Perspective
126. ICML 2026SPA: A Simple but Tough-to-Beat Baseline for Knowledge Injection
127. ICML 2026SpaEF: Spatially Resolved Transcriptomics Data Element-Wise Denoising Framework Powered by Large Models
128. ICML 2026Split Personality Training: Revealing Latent Knowledge Through Alternate Personalities
129. ICML 2026Structure-Centric Graph Foundation Model via Geometric Bases
130. ICML 2026Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search
131. ICML 2026SWING: Unlocking Implicit Graph Representations for Graph Random Features
132. ICML 2026Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection
133. ICML 2026TaskLoom: Weaving Knowledge Across Tasks in World Models
134. ICML 2026The Bridge-Garden Dilemma in LLM Distillation: Why Mixing Hard and Soft Labels Works
135. ICML 2026Torus Graphs for Large Scale Neural Phase Analysis
136. ICML 2026Towards Rule-Based Knowledge Sharing in Federated Learning
137. ICML 2026Towards Universal Gene Regulatory Network Inference: Unlocking Generalizable Regulatory Knowledge in Single-cell Foundation Models
138. ICML 2026Trajectory Seriation via Spectral Tangent Alignment and Global Embedding
139. ICML 2026Unitary Convolutions for Message-passing and Positional Encodings on Directed Graphs
140. ICML 2026Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs
141. ICML 2026Use What You Know: Causal Foundation Models with Partial Graphs
142. ICML 2026View Space: Learning Representation across Arbitrary Graphs
143. ICML 2026Weaving Graph over Tokens: Contextualizing Structured Sequences for LLMs
144. ICML 2026What Makes a Desired Graph for Relational Deep Learning?
145. ICML 2026What Makes a Strong Model? A Unified Spectral Analysis of Knowledge Transfer over High-dimensional Linear Regression
146. ICML 2026When Do Hallucinations Arise? A Graph Perspective on the Evolution of Path Reuse and Path Compression
147. ICML 2026When Shared Knowledge Hurts: Spectral Over-Accumulation in Model Merging
148. ICML 2026XDomainBench: Diagnosing Reasoning Collapse in High-Dimensional Scientific Knowledge Composition
149. ICML 2026XPERT: Expert Knowledge Transfer for Effective Training of Language Models

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.