混合专家论文趋势 2023–2026

主要结论

• 混合专家论文从 2023 年的 236 篇增长到 2026 年的 326 篇，三年间扩大到约 1.4 倍。
• NeurIPS 是发混合专家论文最多的会议，2023–2026 年共 354 篇，占四个会议总量的 39%。
• 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 4 篇增至 2026 年的 79 篇。
• 在「优化与缩放」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的缩放定律是 4.1 倍，混合专家是 1.4 倍。

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 2026A Biconvex Formulation for Stable Transport of Mixture Models with a Unique Solution
• ICML 2026$\phi$-Balancing for Mixture-of-Experts Training
• ICLR 2026A Federated Generalized Expectation-Maximization Algorithm for Mixture Models with an Unknown Number of Components
• CVPR 2026Divide Conquer and Aggregate Asymmetric Experts for Class-Imbalanced Semi-Supervised Medical
• NeurIPS 2025Advancing Expert Specialization for Better MoE
• ICML 2025$\texttt{I$^2$MoE}$: Interpretable Multimodal Interaction-aware Mixture-of-Experts
• ICLR 2025A Sanity Check for AI-generated Image Detection
• CVPR 2025Complexity Experts are Task-Discriminative Learners for Any Image Restoration
• NeurIPS 2024$\texttt{Model-GLUE}$: Democratized LLM Scaling for A Large Model Zoo in the Wild
• ICML 2024$\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts
• ICLR 2024Fusing Models with Complementary Expertise
• CVPR 2024MoDE: CLIP Data Experts via Clustering
• NeurIPS 2023[Re] Numerical influence of ReLU'(0) on backpropagation
• ICML 2023A Distribution Optimization Framework for Confidence Bounds of Risk Measures
• ICLR 2023Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models
• CVPR 2023Balanced Product of Calibrated Experts for Long-Tailed Recognition
• NeurIPS 2026AdERA: Adaptive Exponent Reuse for Lossless Allgather in Sharded MoE Training
• ICML 2026Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse
• ICLR 2026Abstracting Robot Manipulation Skills via Mixture-of-Experts Diffusion Policies
• CVPR 2026ERMoE Eigen-Reparameterized Mixture-of-Experts for Stable Routing and Interpretable Specialization

全部混合专家论文

共 31 篇，第 1 / 1 页

1. ICML 2024$\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts
2. ICML 2024A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
3. ICML 2024A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM)
4. ICML 2024A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts
5. ICML 2024Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
6. ICML 2024Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance
7. ICML 2024BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
8. ICML 2024Convergence of Online Learning Algorithm for a Mixture of Multiple Linear Regressions
9. ICML 2024Efficient Mixture Learning in Black-Box Variational Inference
10. ICML 2024Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs
11. ICML 2024Exploring the Benefit of Activation Sparsity in Pre-training
12. ICML 2024Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
13. ICML 2024Harnessing Hierarchical Label Distribution Variations in Test Agnostic Long-tail Recognition
14. ICML 2024INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
15. ICML 2024Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
16. ICML 2024Learning to Route Among Specialized Experts for Zero-Shot Generalization
17. ICML 2024Merging Multi-Task Models via Weight-Ensembling Mixture of Experts
18. ICML 2024Mixtures of Experts Unlock Parameter Scaling for Deep RL
19. ICML 2024MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
20. ICML 2024On Interpolating Experts and Multi-Armed Bandits
21. ICML 2024On Least Square Estimation in Softmax Gating Mixture of Experts
22. ICML 2024One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
23. ICML 2024OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models
24. ICML 2024Receptive Fields As Experts in Convolutional Neural Architectures
25. ICML 2024Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training
26. ICML 2024Scaling Laws for Fine-Grained Mixture of Experts
27. ICML 2024See More Details: Efficient Image Super-Resolution by Experts Mining
28. ICML 2024Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
29. ICML 2024Theoretical insights for diffusion guidance: A case study for Gaussian mixture models
30. ICML 2024Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts
31. ICML 2024Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models

常见问题

2023–2026 年四大会议一共有多少篇混合专家论文？

共 904 篇，按年份分别是 2023 年 236 篇、2024 年 119 篇、2025 年 223 篇、2026 年 326 篇。

NeurIPS 2026 有多少篇混合专家论文？

NeurIPS 2026 有 75 篇混合专家论文，上一届是 86 篇。

ICLR 2026 有多少篇混合专家论文？

ICLR 2026 有 73 篇混合专家论文，上一届是 59 篇。

ICML 2026 有多少篇混合专家论文？

ICML 2026 有 132 篇混合专家论文，上一届是 57 篇。

CVPR 2026 有多少篇混合专家论文？

CVPR 2026 有 46 篇混合专家论文，上一届是 21 篇。

哪个会议的混合专家论文最多？

NeurIPS，2023–2026 年共 354 篇。