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 6 of 6

251. ICML 2023Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks
252. ICML 2023Mimetic Initialization of Self-Attention Layers
253. ICML 2023Minimax estimation of discontinuous optimal transport maps: The semi-discrete case
254. ICML 2023Mixture Proportion Estimation Beyond Irreducibility
255. ICML 2023Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path
256. ICML 2023Neural networks trained with SGD learn distributions of increasing complexity
257. ICML 2023Neural signature kernels as infinite-width-depth-limits of controlled ResNets
258. ICML 2023Non-asymptotic Properties of Individualized Treatment Rules from Sequentially Rule-Adaptive Trials
259. ICML 2023On Distribution Dependent Sub-Logarithmic Query Time of Learned Indexing
260. ICML 2023On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances
261. ICML 2023On Generalizations of Some Distance Based Classifiers for HDLSS Data
262. ICML 2023On the Convergence Rates of Policy Gradient Methods
263. ICML 2023On the Estimation of Gaussian Mixture Copula Models
264. ICML 2023On the Impact of Algorithmic Recourse on Social Segregation
265. ICML 2023On the Robustness of Randomized Ensembles to Adversarial Perturbations
266. ICML 2023On the Within-Group Fairness of Screening Classifiers
267. ICML 2023Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs
268. ICML 2023Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits
269. ICML 2023Out-of-Domain Robustness via Targeted Augmentations
270. ICML 2023Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks
271. ICML 2023Personalized Federated Learning under Mixture of Distributions
272. ICML 2023Perturbation Analysis of Neural Collapse
273. ICML 2023Phase Transitions in the Detection of Correlated Databases
274. ICML 2023Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models
275. ICML 2023Random Classification Noise does not defeat All Convex Potential Boosters Irrespective of Model Choice
276. ICML 2023Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality
277. ICML 2023Robust Explanation for Free or At the Cost of Faithfulness
278. ICML 2023Statistical Foundations of Prior-Data Fitted Networks
279. ICML 2023The Computational Complexity of Concise Hypersphere Classification
280. ICML 2023The Edge of Orthogonality: A Simple View of What Makes BYOL Tick
281. ICML 2023The multimarginal optimal transport formulation of adversarial multiclass classification
282. ICML 2023The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
283. ICML 2023The Power of Uniform Sampling for k-Median
284. ICML 2023The Test of Tests: A Framework for Differentially Private Hypothesis Testing
285. ICML 2023The Value of Out-of-Distribution Data
286. ICML 2023The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms
287. ICML 2023Theoretical Behavior of XAI Methods in the Presence of Suppressor Variables
288. ICML 2023Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts
289. ICML 2023Under-Counted Tensor Completion with Neural Incorporation of Attributes
290. ICML 2023Understanding Oversquashing in GNNs through the Lens of Effective Resistance
291. ICML 2023Understanding the Impact of Adversarial Robustness on Accuracy Disparity
292. ICML 2023Unit Scaling: Out-of-the-Box Low-Precision Training
293. ICML 2023Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability
294. ICML 2023Unsupervised Out-of-Distribution Detection with Diffusion Inpainting
295. ICML 2023Variational Mixture of HyperGenerators for Learning Distributions over Functions
296. ICML 2023When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction

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.