Mixture of Experts papers, 2023–2026

Key findings

• Mixture of Experts went from 236 papers in 2023 to 326 in 2026, roughly 1.4x in three years.
• NeurIPS publishes the most Mixture of Experts work: 354 papers from 2023 to 2026, 39% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 4 in 2023 to 79 in 2026.
• Among the 5 topics under Optimization and Scaling, it ranks #4 by 2026 paper count; the fastest grower in the group, Scaling Laws, is up 4.1x versus 1.4x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Mixture of Experts papers

296 papers, page 3 of 6

101. ICML 2026Single-Head Attention in High Dimensions: A Theory of Generalization, Weights Spectra, and Scaling Laws
102. ICML 2026Skill-Based Mixture-of-Experts: Adaptive Routing for Heterogeneous Reasoning via Inferred Skills
103. ICML 2026SoftMoE: Soft Differentiable Routing for Mixture-of-Experts in LLMs
104. ICML 2026SPARKLING: Balancing Signal Preservation and Symmetry Breaking for Width-Progressive Learning
105. ICML 2026Sparse Models, Sparse Safety: Unsafe Routes in Mixture-of-Experts LLMs
106. ICML 2026SpecMD: A Comprehensive Study On Speculative Expert Prefetching
107. ICML 2026SPHERE: Mitigating the Loss of Spectral Plasticity in Mixture-of-Experts for Deep Reinforcement Learning
108. ICML 2026Stabilizing MoE Reinforcement Learning by Aligning Training and Inference Routers
109. ICML 2026STAR: Rethinking MoE Routing as Structure-Aware Subspace Learning
110. ICML 2026Synergistic Intra- and Cross-Layer Regularization Losses for MoE Expert Specialization
111. ICML 2026Task-Aware Mechanism: Hybrid MoE Vision Tower Towards Holistic Video Understanding
112. ICML 2026TEAM: Temporal–Spatial Consistency Guided Expert Activation for MoE Diffusion Language Model Acceleration
113. ICML 2026The Catastrophic Failure of *the* k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It
114. ICML 2026The Cost of Commitment in Option-Based Hierarchical RL
115. ICML 2026The Expert Strikes Back: Interpreting Mixture-of-Experts Language Models at Expert Level
116. ICML 2026TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling
117. ICML 2026TIME: Tensor-Factorized Mixture-of-Experts with Intrinsic Routing for Lifelong Multimodal Knowledge Editing
118. ICML 2026TiME: Test-Time Mixture-of-Experts Routing via Asymmetric CO-Optimal Transport for Continual Test-Time Adaptation
119. ICML 2026TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts
120. ICML 2026Toward Calibrated Mixture-of-Experts Under Distribution Shift
121. ICML 2026Toward Structural Multimodal Representations: Specialization, Selection, and Sparsification via Mixture-of-Experts
122. ICML 2026Towards a Unified Generative Model for Scarce Time Series with Domain Experts
123. ICML 2026Towards One-for-All Anomaly Detection for Tabular Data
124. ICML 2026TRACE: Trajectory Recovery for Continuous Mechanism Evolution in Causal Representation Learning
125. ICML 2026UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models
126. ICML 2026Unified Multimodal Visual Tracking with Dual Mixture-of-Experts
127. ICML 2026Variational Routing: A Scalable Bayesian Framework for Calibrated Mixture-of-Experts Transformers
128. ICML 2026WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems
129. ICML 2026When Model Merging Breaks Routing: Training-Free Calibration for MoE
130. ICML 2026When More Experts Hurt: Underfitting in Multi-Expert Learning to Defer
131. ICML 2026X-MoGe: A Cross-Modal Adaptation Framework with Mixture-of-Experts and Geometry Guidance for Heterogeneous Collaborative Perception
132. ICML 2026ZipMoE: Efficient On-Device MoE Serving via Lossless Compression and Cache-Affinity Scheduling
133. ICML 2025$\texttt{I$^2$MoE}$: Interpretable Multimodal Interaction-aware Mixture-of-Experts
134. ICML 2025A Generic Family of Graphical Models: Diversity, Efficiency, and Heterogeneity
135. ICML 2025A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
136. ICML 2025Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
137. ICML 2025Autonomy-of-Experts Models
138. ICML 2025Bayesian Inference for Correlated Human Experts and Classifiers
139. ICML 2025Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning
140. ICML 2025Cooperation of Experts: Fusing Heterogeneous Information with Large Margin
141. ICML 2025DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts
142. ICML 2025Delta Decompression for MoE-based LLMs Compression
143. ICML 2025Diff-MoE: Diffusion Transformer with Time-Aware and Space-Adaptive Experts
144. ICML 2025Domain2Vec: Vectorizing Datasets to Find the Optimal Data Mixture without Training
145. ICML 2025Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning
146. ICML 2025Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts
147. ICML 2025FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification
148. ICML 2025FloE: On-the-Fly MoE Inference on Memory-constrained GPU
149. ICML 2025Gaussian Mixture Flow Matching Models
150. ICML 2025Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation

FAQ

How many Mixture of Experts papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

904 in total: 236 in 2023, 119 in 2024, 223 in 2025, 326 in 2026.

How many Mixture of Experts papers are at NeurIPS 2026?

NeurIPS 2026 has 75 Mixture of Experts papers, versus 86 the year before.

How many Mixture of Experts papers are at ICLR 2026?

ICLR 2026 has 73 Mixture of Experts papers, versus 59 the year before.

How many Mixture of Experts papers are at ICML 2026?

ICML 2026 has 132 Mixture of Experts papers, versus 57 the year before.

How many Mixture of Experts papers are at CVPR 2026?

CVPR 2026 has 46 Mixture of Experts papers, versus 21 the year before.

Which conference publishes the most Mixture of Experts papers?

NeurIPS, with 354 papers from 2023 to 2026.