混合专家论文趋势 2023–2026
MoE 路由与训练
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 904 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 138 | 16 | 76 | 6 | 236 |
| 2024 | 55 | 24 | 31 | 9 | 119 |
| 2025 | 86 | 59 | 57 | 21 | 223 |
| 2026 | 75 | 73 | 132 | 46 | 326 |
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 904 篇，第 7 / 19 页
- NeurIPS 2026MoTo: Mixture of Tokenizers Towards Fair Multilingual Language Modeling
- NeurIPS 2026Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer
- NeurIPS 2026N-vium: Mixture-of-Exits Transformer for Accelerated Exact Generation
- NeurIPS 2026Non-Expanding Gated Continued Fraction Architecture for Feedforward Layers in Language Models
- NeurIPS 2026Not All Routing Drift Is Harmful: Trust-Region Projection for Class-Incremental Learning
- NeurIPS 2026One-Bit Clustering for Two Component Sub-Gaussian Mixture Models
- NeurIPS 2026PGMS: Pyramidal Gaussian Mixture Splatting for 3DGS Compression
- NeurIPS 2026Physics-Informed Video Generation via Mixture-of-Experts Latent Alignment
- NeurIPS 2026PithTrain: A Compact and Agent-Native MoE Training System
- NeurIPS 2026POISE: Instance-Specific Prompt Tuning under Latent Mixture Target Distributions
- NeurIPS 2026Predicting Only from Selected Evidence: A Tempered Product-of-Experts Bottleneck for Auditable EEG Diagnosis
- NeurIPS 2026PriSM: Prior-guided Shared-basis Mixture Personalization for LLMs under Sparse User Histories
- NeurIPS 2026Private Online Prediction from Experts with Small Losses
- NeurIPS 2026Raw-Routed Mixture of Adapters: A Causal Intervention for Routing Collapse in Time Series Foundation Models
- NeurIPS 2026Replicas-as-Variables: A Planner for Throughput-Optimal Routing in LLM Deployment
- NeurIPS 2026Residual Paving: Diagnosing the Routing Bottleneck in Selective Refusal Editing
- NeurIPS 2026Route-Consistent Adaptation for Stable Quantization of Mixture-of-Experts Models with Theoretical Guarantees
- NeurIPS 2026S²MoE: Shared-Subspace Mixture of Sparse Experts
- NeurIPS 2026SAME: Stability-Aware Embedding Extraction in Mixture-of-Experts Language Models
- NeurIPS 2026SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization
- NeurIPS 2026Spectral Geometry of Attention: From Information Routing to Uncertainty
- NeurIPS 2026Structure, Subspace and System: Push the Real Limit of Extremely Low-Bit Quantization for MoE-LLMs
- NeurIPS 2026Swimba: Switch Mamba Model Scales State Space Models
- NeurIPS 2026Training-Free Dynamic Upcycling of Expert Language Models
- NeurIPS 2026vExpert: Virtualizing Expert Storage for Adaptive Load Balancing in Distributed MoE Inference
- NeurIPS 2026Why Routers Freeze: Infinite Width Learning Dynamics for Mixture of Experts
- CVPR 2025CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering
- CVPR 2025CMMLoc: Advancing Text-to-PointCloud Localization with Cauchy-Mixture-Model Based Framework
- CVPR 2025Complexity Experts are Task-Discriminative Learners for Any Image Restoration
- CVPR 2025DeRS: Towards Extremely Efficient Upcycled Mixture-of-Experts Models
- CVPR 2025dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis
- CVPR 2025Efficient Data Driven Mixture-of-Expert Extraction from Trained Networks
- CVPR 2025EMOE: Modality-Specific Enhanced Dynamic Emotion Experts
- CVPR 2025Enhancing Online Continual Learning with Plug-and-Play State Space Model and Class-Conditional Mixture of Discretization
- CVPR 2025Learning Heterogeneous Tissues with Mixture of Experts for Gigapixel Whole Slide Images
- CVPR 2025Learning on Model Weights using Tree Experts
- CVPR 2025Lifelong Knowledge Editing for Vision Language Models with Low-Rank Mixture-of-Experts
- CVPR 2025LiMoE: Mixture of LiDAR Representation Learners from Automotive Scenes
- CVPR 2025Mixture of Submodules for Domain Adaptive Person Search
- CVPR 2025MoEE: Mixture of Emotion Experts for Audio-Driven Portrait Animation
- CVPR 2025MoVE-KD: Knowledge Distillation for VLMs with Mixture of Visual Encoders
- CVPR 2025Object Detection using Event Camera: A MoE Heat Conduction based Detector and A New Benchmark Dataset
- CVPR 2025pFedMxF: Personalized Federated Class-Incremental Learning with Mixture of Frequency Aggregation
- CVPR 2025Question-Aware Gaussian Experts for Audio-Visual Question Answering
- CVPR 2025Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning
- CVPR 2025SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking
- CVPR 2025V^2Dial: Unification of Video and Visual Dialog via Multimodal Experts
- ICLR 2025A Sanity Check for AI-generated Image Detection
- ICLR 2025Ada-K Routing: Boosting the Efficiency of MoE-based LLMs
- ICLR 2025Balancing Act: Diversity and Consistency in Large Language Model Ensembles
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 查混合专家在 NeurIPS 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": "mixture-of-experts"}
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。