Mixture of Experts Explained

Mixtral of experts

Mixture of Experts (MoEs) in Transformers

Machine Learning Experts - Sasha Luccioni

Introducing Mellum2: A 12B Mixture-of-Experts Model by JetBrains

Machine Learning Experts - Margaret Mitchell

Robustness of Mixtures of Experts to Feature Noise

arXiv:2601. 14792v2 Announce Type: replace Abstract: Despite their practical success, it remains unclear why Mixture of Experts (MoE) models can outperform dense networks beyond sheer parameter scaling.

PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization

arXiv:2606. 03444v1 Announce Type: cross Abstract: Unifying the complementary strengths of diverse Vision Foundation Models (VFMs) into a single efficient model is highly desirable but challenged by the negative transfer inherent in monolithic distillation.

Machine Learning Experts - Lewis Tunstall

A Heterogeneous Mixture of Experts Framework for Interpretable Machine Learning

arXiv:2608.24195v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models provide a flexible framework for partitioning complex prediction problems into simpler local learning tasks through a...

Knowledge Injection Exists in MoE? Exploring Expert-Aware Contrast Decoding in MoE for Mitigating LLMs'Hallucinations

arXiv:2607. 20426v1 Announce Type: cross Abstract: Existing LLM hallucination mitigation methods, including prompt engineering and model optimization, either hardly alter models'internal knowledge or have poor cross-domain generalization.

Beyond Magnitude: Contrastive Routing for Modular Mixture-of-Experts

In current Mixture-of-Experts architectures, routing is performed based on representations dominated by structure shared across all tokens, limiting expert specialization. We show that contrasting eac...

A theoretical model for task routing in mixture-of-expert transformers

arXiv:2606. 14398v1 Announce Type: new Abstract: Mixture-of-experts (MoE) layers enable the scaling of transformer models while keeping the inference compute fixed.