Saved in:
| Main Authors: | Jing, Linglin, Gao, Yuting, Wang, Zhigang, Lan, Wang, Tang, Yiwen, Wang, Wenhai, Zhang, Kaipeng, Guo, Qingpei |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.23830 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
OrdMoE: Preference Alignment via Hierarchical Expert Group Ranking in Multimodal Mixture-of-Experts LLMs
by: Gao, Yuting, et al.
Published: (2025)
by: Gao, Yuting, et al.
Published: (2025)
AnyExperts: On-Demand Expert Allocation for Multimodal Language Models with Mixture of Expert
by: Gao, Yuting, et al.
Published: (2025)
by: Gao, Yuting, et al.
Published: (2025)
LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models
by: Zhao, Hengyuan, et al.
Published: (2025)
by: Zhao, Hengyuan, et al.
Published: (2025)
FourierMoE: Fourier Mixture-of-Experts Adaptation of Large Language Models
by: Jiang, Juyong, et al.
Published: (2026)
by: Jiang, Juyong, et al.
Published: (2026)
MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping
by: Huang, Yushi, et al.
Published: (2025)
by: Huang, Yushi, et al.
Published: (2025)
A Survey on Mixture of Experts in Large Language Models
by: Cai, Weilin, et al.
Published: (2024)
by: Cai, Weilin, et al.
Published: (2024)
Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language Models
by: Guo, Hongcheng, et al.
Published: (2025)
by: Guo, Hongcheng, et al.
Published: (2025)
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
by: Dai, Damai, et al.
Published: (2024)
by: Dai, Damai, et al.
Published: (2024)
BLR-MoE: Boosted Language-Routing Mixture of Experts for Domain-Robust Multilingual E2E ASR
by: Ma, Guodong, et al.
Published: (2025)
by: Ma, Guodong, et al.
Published: (2025)
DIVE into MoE: Diversity-Enhanced Reconstruction of Large Language Models from Dense into Mixture-of-Experts
by: Feng, Yuchen, et al.
Published: (2025)
by: Feng, Yuchen, et al.
Published: (2025)
Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity
by: Tang, Yehui, et al.
Published: (2025)
by: Tang, Yehui, et al.
Published: (2025)
$μ$-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts
by: Koike-Akino, Toshiaki, et al.
Published: (2025)
by: Koike-Akino, Toshiaki, et al.
Published: (2025)
MoE-LPR: Multilingual Extension of Large Language Models through Mixture-of-Experts with Language Priors Routing
by: Zhou, Hao, et al.
Published: (2024)
by: Zhou, Hao, et al.
Published: (2024)
Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts
by: Li, Yunxin, et al.
Published: (2024)
by: Li, Yunxin, et al.
Published: (2024)
$\infty$-MoE: Generalizing Mixture of Experts to Infinite Experts
by: Takashiro, Shota, et al.
Published: (2026)
by: Takashiro, Shota, et al.
Published: (2026)
MultiPL-MoE: Multi-Programming-Lingual Extension of Large Language Models through Hybrid Mixture-of-Experts
by: Wang, Qing, et al.
Published: (2025)
by: Wang, Qing, et al.
Published: (2025)
Marco-MoE: Open Multilingual Mixture-of-Expert Language Models with Efficient Upcycling
by: Jiang, Fan, et al.
Published: (2026)
by: Jiang, Fan, et al.
Published: (2026)
ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning
by: Gao, Shangqian, et al.
Published: (2025)
by: Gao, Shangqian, et al.
Published: (2025)
Unveiling Super Experts in Mixture-of-Experts Large Language Models
by: Su, Zunhai, et al.
Published: (2025)
by: Su, Zunhai, et al.
Published: (2025)
Linear-MoE: Linear Sequence Modeling Meets Mixture-of-Experts
by: Sun, Weigao, et al.
Published: (2025)
by: Sun, Weigao, et al.
Published: (2025)
TiMoE: Time-Aware Mixture of Language Experts
by: Faro, Robin, et al.
Published: (2025)
by: Faro, Robin, et al.
Published: (2025)
LEMoE: Advanced Mixture of Experts Adaptor for Lifelong Model Editing of Large Language Models
by: Wang, Renzhi, et al.
Published: (2024)
by: Wang, Renzhi, et al.
Published: (2024)
HMoE: Heterogeneous Mixture of Experts for Language Modeling
by: Wang, An, et al.
Published: (2024)
by: Wang, An, et al.
Published: (2024)
Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference
by: Liu, Baihui, et al.
Published: (2026)
by: Liu, Baihui, et al.
Published: (2026)
MoBiLE: Efficient Mixture-of-Experts Inference on Consumer GPU with Mixture of Big Little Experts
by: Zhao, Yushu, et al.
Published: (2025)
by: Zhao, Yushu, et al.
Published: (2025)
MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router
by: Xie, Yanyue, et al.
Published: (2024)
by: Xie, Yanyue, et al.
Published: (2024)
Elastic MoE: Unlocking the Inference-Time Scalability of Mixture-of-Experts
by: Gu, Naibin, et al.
Published: (2025)
by: Gu, Naibin, et al.
Published: (2025)
Mixture of Lookup Experts
by: Jie, Shibo, et al.
Published: (2025)
by: Jie, Shibo, et al.
Published: (2025)
A Closer Look into Mixture-of-Experts in Large Language Models
by: Lo, Ka Man, et al.
Published: (2024)
by: Lo, Ka Man, et al.
Published: (2024)
MoDEM: Mixture of Domain Expert Models
by: Simonds, Toby, et al.
Published: (2024)
by: Simonds, Toby, et al.
Published: (2024)
SEER-MoE: Sparse Expert Efficiency through Regularization for Mixture-of-Experts
by: Muzio, Alexandre, et al.
Published: (2024)
by: Muzio, Alexandre, et al.
Published: (2024)
When Are Experts Misrouted? Counterfactual Routing Analysis in Mixture-of-Experts Language Models
by: Yoon, Youngsik, et al.
Published: (2026)
by: Yoon, Youngsik, et al.
Published: (2026)
MH-MoE: Multi-Head Mixture-of-Experts
by: Huang, Shaohan, et al.
Published: (2024)
by: Huang, Shaohan, et al.
Published: (2024)
Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models
by: Wei, Tianwen, et al.
Published: (2024)
by: Wei, Tianwen, et al.
Published: (2024)
Mixture of Heterogeneous Grouped Experts for Language Modeling
by: Ma, Zhicheng, et al.
Published: (2026)
by: Ma, Zhicheng, et al.
Published: (2026)
Bayesian Mixture of Experts For Large Language Models
by: Dialameh, Maryam, et al.
Published: (2025)
by: Dialameh, Maryam, et al.
Published: (2025)
MMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction Experts
by: Yu, Haofei, et al.
Published: (2023)
by: Yu, Haofei, et al.
Published: (2023)
MEMoE: Enhancing Model Editing with Mixture of Experts Adaptors
by: Wang, Renzhi, et al.
Published: (2024)
by: Wang, Renzhi, et al.
Published: (2024)
Pre-Attention Expert Prediction and Prefetching for Mixture-of-Experts Large Language Models
by: Zhu, Shien, et al.
Published: (2025)
by: Zhu, Shien, et al.
Published: (2025)
Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment
by: Liu, Zhili, et al.
Published: (2024)
by: Liu, Zhili, et al.
Published: (2024)
Similar Items
-
OrdMoE: Preference Alignment via Hierarchical Expert Group Ranking in Multimodal Mixture-of-Experts LLMs
by: Gao, Yuting, et al.
Published: (2025) -
AnyExperts: On-Demand Expert Allocation for Multimodal Language Models with Mixture of Expert
by: Gao, Yuting, et al.
Published: (2025) -
LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models
by: Zhao, Hengyuan, et al.
Published: (2025) -
FourierMoE: Fourier Mixture-of-Experts Adaptation of Large Language Models
by: Jiang, Juyong, et al.
Published: (2026) -
MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping
by: Huang, Yushi, et al.
Published: (2025)