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 154 篇,第 1 / 4 页
- NeurIPS 2025$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
- NeurIPS 2025A CLT for Polynomial GNNs on Community-Based Graphs
- NeurIPS 2025A Pre-training Framework for Relational Data with Information-theoretic Principles
- NeurIPS 2025A Signed Graph Approach to Understanding and Mitigating Oversmoothing
- NeurIPS 2025A Token is Worth over 1,000 Tokens: Efficient Knowledge Distillation through Low-Rank Clone
- NeurIPS 2025AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders
- NeurIPS 2025Adjusted Count Quantification Learning on Graphs
- NeurIPS 2025Angular Constraint Embedding via SpherePair Loss for Constrained Clustering
- NeurIPS 2025Black-Box Membership Inference Attack for LVLMs via Prior Knowledge-Calibrated Memory Probing
- NeurIPS 2025C$^2$Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning
- NeurIPS 2025Can Knowledge-Graph-based Retrieval Augmented Generation Really Retrieve What You Need?
- NeurIPS 2025Characterization and Learning of Causal Graphs from Hard Interventions
- NeurIPS 2025Co-Regularization Enhances Knowledge Transfer in High Dimensions
- NeurIPS 2025Codifying Character Logic in Role-Playing
- NeurIPS 2025Conditional Diffusion Anomaly Modeling on Graphs
- NeurIPS 2025Conflict-Aware Knowledge Editing in the Wild: Semantic-Augmented Graph Representation for Unstructured Text
- NeurIPS 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
- NeurIPS 2025Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models
- NeurIPS 2025Curriculum Abductive Learning
- NeurIPS 2025Data Mixing Can Induce Phase Transitions in Knowledge Acquisition
- NeurIPS 2025DCA: Graph-Guided Deep Embedding Clustering for Brain Atlases
- NeurIPS 2025Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models
- NeurIPS 2025DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation Trainer
- NeurIPS 2025Defining and Discovering Hyper-meta-paths for Heterogeneous Hypergraphs
- NeurIPS 2025Deliberation on Priors: Trustworthy Reasoning of Large Language Models on Knowledge Graphs
- NeurIPS 2025Democratizing Clinical Risk Prediction with Cross-Cohort Cross-Modal Knowledge Transfer
- NeurIPS 2025Dependency Matters: Enhancing LLM Reasoning with Explicit Knowledge Grounding
- NeurIPS 2025Diagnosing and Addressing Pitfalls in KG-RAG Datasets: Toward More Reliable Benchmarking
- NeurIPS 2025Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search
- NeurIPS 2025Distribution Learning Meets Graph Structure Sampling
- NeurIPS 2025DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning
- NeurIPS 2025Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
- NeurIPS 2025DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning with Dual-Pathway Global-Local Fusion
- NeurIPS 2025DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs
- NeurIPS 2025Dynamic Bundling with Large Language Models for Zero-Shot Inference on Text-Attributed Graphs
- NeurIPS 2025Edit Less, Achieve More: Dynamic Sparse Neuron Masking for Lifelong Knowledge Editing in LLMs
- NeurIPS 2025Efficient Knowledge Transfer in Federated Recommendation for Joint Venture Ecosystem
- NeurIPS 2025Efficient Verified Unlearning For Distillation
- NeurIPS 2025Elastic Robust Unlearning of Specific Knowledge in Large Language Models
- NeurIPS 2025Elevating Visual Perception in Multimodal LLMs with Visual Embedding Distillation
- NeurIPS 2025Embeddings as Probabilistic Equivalence in Logic Programs
- NeurIPS 2025Enhancing LLM Planning for Robotics Manipulation through Hierarchical Procedural Knowledge Graphs
- NeurIPS 2025Estimating Hitting Times Locally at Scale
- NeurIPS 2025Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning
- NeurIPS 2025Exact and Linear Convergence for Federated Learning under Arbitrary Client Participation is Attainable
- NeurIPS 2025Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior
- NeurIPS 2025Far from the Shallow: Brain-Predictive Reasoning Embedding through Residual Disentanglement
- NeurIPS 2025FedFree: Breaking Knowledge-sharing Barriers through Layer-wise Alignment in Heterogeneous Federated Learning
- NeurIPS 2025FedIGL: Federated Invariant Graph Learning for Non-IID Graphs
- NeurIPS 2025Fin3R: Fine-tuning Feed-forward 3D Reconstruction Models via Monocular Knowledge Distillation
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。