Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Zihan, Pan, Rui, Yao, Jiarui, Csordas, Robert, Li, Linjie, Yin, Lu, Wu, Jiajun, Zhang, Tong, Li, Manling, Liu, Shiwei |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Rewiring Experts on the Fly:Continuous Rerouting for Better Online Adaptation in Mixture-of-Expert models
by: Su, Guinan, et al.
Published: (2025)
by: Su, Guinan, et al.
Published: (2025)
SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention
by: Csordás, Róbert, et al.
Published: (2023)
by: Csordás, Róbert, et al.
Published: (2023)
Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing
by: Piękos, Piotr, et al.
Published: (2025)
by: Piękos, Piotr, et al.
Published: (2025)
Group then Scale: Dynamic Mixture-of-Experts Multilingual Language Model
by: Li, Chong, et al.
Published: (2025)
by: Li, Chong, 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)
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)
Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models
by: Lu, Xudong, et al.
Published: (2024)
by: Lu, Xudong, et al.
Published: (2024)
Understanding and Leveraging the Expert Specialization of Context Faithfulness in Mixture-of-Experts LLMs
by: Bai, Jun, et al.
Published: (2025)
by: Bai, Jun, et al.
Published: (2025)
ReXMoE: Reusing Experts with Minimal Overhead in Mixture-of-Experts
by: Tan, Zheyue, et al.
Published: (2025)
by: Tan, Zheyue, et al.
Published: (2025)
Router Upcycling: Leveraging Mixture-of-Routers in Mixture-of-Experts Upcycling
by: Ran, Junfeng, et al.
Published: (2025)
by: Ran, Junfeng, et al.
Published: (2025)
Scalable Model Editing via Customized Expert Networks
by: Yao, Zihan, et al.
Published: (2024)
by: Yao, Zihan, et al.
Published: (2024)
XFT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts
by: Ding, Yifeng, et al.
Published: (2024)
by: Ding, Yifeng, et al.
Published: (2024)
Unveiling Super Experts in Mixture-of-Experts Large Language Models
by: Su, Zunhai, et al.
Published: (2025)
by: Su, Zunhai, et al.
Published: (2025)
Layerwise Recurrent Router for Mixture-of-Experts
by: Qiu, Zihan, et al.
Published: (2024)
by: Qiu, Zihan, et al.
Published: (2024)
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models
by: Pan, Zhenyu, et al.
Published: (2024)
by: Pan, Zhenyu, et al.
Published: (2024)
Maximum Score Routing For Mixture-of-Experts
by: Dong, Bowen, et al.
Published: (2025)
by: Dong, Bowen, 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)
MoPE: Mixture of Prefix Experts for Zero-Shot Dialogue State Tracking
by: Tang, Tianwen, et al.
Published: (2024)
by: Tang, Tianwen, et al.
Published: (2024)
Mixture of Lookup Experts
by: Jie, Shibo, et al.
Published: (2025)
by: Jie, Shibo, et al.
Published: (2025)
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)
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)
Upcycling Large Language Models into Mixture of Experts
by: He, Ethan, et al.
Published: (2024)
by: He, Ethan, et al.
Published: (2024)
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)
Scalable Training of Mixture-of-Experts Models with Megatron Core
by: Yan, Zijie, et al.
Published: (2026)
by: Yan, Zijie, et al.
Published: (2026)
SciDFM: A Large Language Model with Mixture-of-Experts for Science
by: Sun, Liangtai, et al.
Published: (2024)
by: Sun, Liangtai, et al.
Published: (2024)
Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models
by: Qiu, Zihan, et al.
Published: (2025)
by: Qiu, Zihan, et al.
Published: (2025)
MEMoE: Enhancing Model Editing with Mixture of Experts Adaptors
by: Wang, Renzhi, et al.
Published: (2024)
by: Wang, Renzhi, et al.
Published: (2024)
Mixture Compressor for Mixture-of-Experts LLMs Gains More
by: Huang, Wei, et al.
Published: (2024)
by: Huang, Wei, et al.
Published: (2024)
Exploiting Mixture-of-Experts Redundancy Unlocks Multimodal Generative Abilities
by: Dutt, Raman, et al.
Published: (2025)
by: Dutt, Raman, et al.
Published: (2025)
Conv-CoA: Improving Open-domain Question Answering in Large Language Models via Conversational Chain-of-Action
by: Pan, Zhenyu, et al.
Published: (2024)
by: Pan, Zhenyu, et al.
Published: (2024)
GatePro: Parameter-Free Expert Selection Optimization for Mixture-of-Experts Models
by: Zheng, Chen, et al.
Published: (2025)
by: Zheng, Chen, et al.
Published: (2025)
DiEP: Adaptive Mixture-of-Experts Compression through Differentiable Expert Pruning
by: Bai, Sikai, et al.
Published: (2025)
by: Bai, Sikai, et al.
Published: (2025)
Mixture of Neuron Experts
by: Cheng, Runxi, et al.
Published: (2025)
by: Cheng, Runxi, et al.
Published: (2025)
Preserving Long-Tailed Expert Information in Mixture-of-Experts Tuning
by: He, Haoze, et al.
Published: (2026)
by: He, Haoze, et al.
Published: (2026)
Modality Interactive Mixture-of-Experts for Fake News Detection
by: Liu, Yifan, et al.
Published: (2025)
by: Liu, Yifan, et al.
Published: (2025)
Mixture of LoRA Experts
by: Wu, Xun, et al.
Published: (2024)
by: Wu, Xun, et al.
Published: (2024)
ExpertFlow: Efficient Mixture-of-Experts Inference via Predictive Expert Caching and Token Scheduling
by: He, Xin, et al.
Published: (2024)
by: He, Xin, et al.
Published: (2024)
MoEUT: Mixture-of-Experts Universal Transformers
by: Csordás, Róbert, et al.
Published: (2024)
by: Csordás, Róbert, et al.
Published: (2024)
Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free
by: Li, Ziyue, et al.
Published: (2024)
by: Li, Ziyue, et al.
Published: (2024)
Multi-Head Mixture-of-Experts
by: Wu, Xun, et al.
Published: (2024)
by: Wu, Xun, et al.
Published: (2024)
Similar Items
-
Rewiring Experts on the Fly:Continuous Rerouting for Better Online Adaptation in Mixture-of-Expert models
by: Su, Guinan, et al.
Published: (2025) -
SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention
by: Csordás, Róbert, et al.
Published: (2023) -
Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing
by: Piękos, Piotr, et al.
Published: (2025) -
Group then Scale: Dynamic Mixture-of-Experts Multilingual Language Model
by: Li, Chong, 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)