知识图谱论文趋势 2023–2026
图谱嵌入与推理
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 1,715 篇被归入该主题的论文。
主要结论
- 知识图谱论文从 2023 年的 287 篇增长到 2026 年的 536 篇,三年间扩大到约 1.9 倍。
- ICLR 是发知识图谱论文最多的会议,2023–2026 年共 571 篇,占四个会议总量的 33%。
- 交叉方向里涨得最快的是多模态大模型:同时属于两个主题的论文从 2023 年的 17 篇增至 2026 年的 93 篇。
- 在「图与结构化数据」的 5 个主题里,它的 2026 年论文数排第 2;同组增长最快的时间序列是 3.2 倍,知识图谱是 1.9 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 76 | 78 | 72 | 61 | 287 |
| 2024 | 153 | 120 | 103 | 50 | 426 |
| 2025 | 154 | 172 | 99 | 41 | 466 |
| 2026 | 133 | 201 | 149 | 53 | 536 |
代表论文
按年份和会议均匀挑选,方便快速看到每一届的样貌
- 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
全部知识图谱论文
共 536 篇,第 8 / 11 页
- ICML 2026Neural Feature Geometry Evolves as Discrete Ricci Flow
- ICML 2026On Efficient Scaling of GNNs via IO-Aware Layers Implementations
- ICML 2026On the Origin of Neural Scaling Laws: from Random Graphs to Natural Language
- ICML 2026On the Spectral Unreachability of Brain Graph Learning
- ICML 2026On the Theoretical Limitations of Embedding-based Link Prediction
- ICML 2026PACER: Acyclic Causal Discovery from Large-scale Interventional Data
- ICML 2026PADD: Path-Aligned Decompression Distillation for Non-Router Teacher to Guide MoE Student Learning
- ICML 2026Parametrized Power-Iteration Clustering for Directed Graphs
- ICML 2026Plain Transformers are Surprisingly Powerful Link Predictors
- ICML 2026PPI Candidate Ranking: Large-Scale Evaluation of a Domain Knowledge–Guided Pipeline
- ICML 2026PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs
- ICML 2026Provable Accuracy Collapse of Embedding-Based Representations under Dimensionality Mismatch
- ICML 2026Quantifying Cross-Domain Knowledge Distillation in the Presence of Domain Shift
- ICML 2026REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment
- ICML 2026Reasoning Structure of Large Language Models
- ICML 2026Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding
- ICML 2026Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle
- ICML 2026Rethinking Graph Transformers as Graph Signal Denoisers: The Role of Block-Diagonal Priors
- ICML 2026Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence
- ICML 2026Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing
- ICML 2026Robust Signal Enhancement via Fractional Detail Views and Knowledge Guided Multi-view Fusion
- ICML 2026Rotary Position Encodings for Graphs
- ICML 2026RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation
- ICML 2026Scalable Topology-Preserving Graph Coarsening: Concepts and Algorithms
- ICML 2026Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration
- ICML 2026Semi-Supervised Learning for Molecular Graphs via Ensemble Consensus
- ICML 2026Semi-Supervised Noise Adaptation: Transferring Knowledge from Noise Domain
- ICML 2026SG2Loc: Sequential Visual Localization on 3D Scene Graphs
- ICML 2026Size Transferability of Graph Convolutional Networks across Sparsity: A Generalized Graphon Perspective
- ICML 2026SPA: A Simple but Tough-to-Beat Baseline for Knowledge Injection
- ICML 2026SpaEF: Spatially Resolved Transcriptomics Data Element-Wise Denoising Framework Powered by Large Models
- ICML 2026Split Personality Training: Revealing Latent Knowledge Through Alternate Personalities
- ICML 2026Structure-Centric Graph Foundation Model via Geometric Bases
- ICML 2026Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search
- ICML 2026SWING: Unlocking Implicit Graph Representations for Graph Random Features
- ICML 2026Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection
- ICML 2026TaskLoom: Weaving Knowledge Across Tasks in World Models
- ICML 2026The Bridge-Garden Dilemma in LLM Distillation: Why Mixing Hard and Soft Labels Works
- ICML 2026Torus Graphs for Large Scale Neural Phase Analysis
- ICML 2026Towards Rule-Based Knowledge Sharing in Federated Learning
- ICML 2026Towards Universal Gene Regulatory Network Inference: Unlocking Generalizable Regulatory Knowledge in Single-cell Foundation Models
- ICML 2026Trajectory Seriation via Spectral Tangent Alignment and Global Embedding
- ICML 2026Unitary Convolutions for Message-passing and Positional Encodings on Directed Graphs
- ICML 2026Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs
- ICML 2026Use What You Know: Causal Foundation Models with Partial Graphs
- ICML 2026View Space: Learning Representation across Arbitrary Graphs
- ICML 2026Weaving Graph over Tokens: Contextualizing Structured Sequences for LLMs
- ICML 2026What Makes a Desired Graph for Relational Deep Learning?
- ICML 2026What Makes a Strong Model? A Unified Spectral Analysis of Knowledge Transfer over High-dimensional Linear Regression
- ICML 2026When Do Hallucinations Arise? A Graph Perspective on the Evolution of Path Reuse and Path Compression
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查知识图谱在 ICLR 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "knowledge-graphs"}
常见问题
- 2023–2026 年四大会议一共有多少篇知识图谱论文?
- 共 1,715 篇,按年份分别是 2023 年 287 篇、2024 年 426 篇、2025 年 466 篇、2026 年 536 篇。
- NeurIPS 2026 有多少篇知识图谱论文?
- NeurIPS 2026 有 133 篇知识图谱论文,上一届是 154 篇。
- ICLR 2026 有多少篇知识图谱论文?
- ICLR 2026 有 201 篇知识图谱论文,上一届是 172 篇。
- ICML 2026 有多少篇知识图谱论文?
- ICML 2026 有 149 篇知识图谱论文,上一届是 99 篇。
- CVPR 2026 有多少篇知识图谱论文?
- CVPR 2026 有 53 篇知识图谱论文,上一届是 41 篇。
- 哪个会议的知识图谱论文最多?
- ICLR,2023–2026 年共 571 篇。