Bayesian Mixture of Experts For Large Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Dialameh, Maryam, Rajabzadeh, Hossein, Zhang, Weiwei, Ahmed, Walid, Kwon, Hyock Ju |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ECHO-LLaMA: Efficient Caching for High-Performance LLaMA Training
by: Dialameh, Maryam, et al.
Published: (2025)
by: Dialameh, Maryam, et al.
Published: (2025)
FLOP-Efficient Training: Early Stopping Based on Test-Time Compute Awareness
by: Amer, Hossam, et al.
Published: (2026)
by: Amer, Hossam, et al.
Published: (2026)
LoRA-Drop: Temporal LoRA Decoding for Efficient LLM Inference
by: Rajabzadeh, Hossein, et al.
Published: (2026)
by: Rajabzadeh, Hossein, et al.
Published: (2026)
EchoAtt: Attend, Copy, then Adjust for More Efficient Large Language Models
by: Rajabzadeh, Hossein, et al.
Published: (2024)
by: Rajabzadeh, Hossein, et al.
Published: (2024)
QDyLoRA: Quantized Dynamic Low-Rank Adaptation for Efficient Large Language Model Tuning
by: Rajabzadeh, Hossein, et al.
Published: (2024)
by: Rajabzadeh, Hossein, et al.
Published: (2024)
EMA-SAM: Exponential Moving-average for SAM-based PTMC Segmentation
by: Dialameh, Maryam, et al.
Published: (2025)
by: Dialameh, Maryam, et al.
Published: (2025)
DualSwinUnet++: An Enhanced Swin-Unet Architecture With Dual Decoders For PTMC Segmentation
by: Dialameh, Maryam, et al.
Published: (2024)
by: Dialameh, Maryam, et al.
Published: (2024)
A Survey on Mixture of Experts in Large Language Models
by: Cai, Weilin, et al.
Published: (2024)
by: Cai, Weilin, et al.
Published: (2024)
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)
Upcycling Large Language Models into Mixture of Experts
by: He, Ethan, et al.
Published: (2024)
by: He, Ethan, et al.
Published: (2024)
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)
EPAS: Efficient Training with Progressive Activation Sharing
by: Karim, Rezaul, et al.
Published: (2026)
by: Karim, Rezaul, et al.
Published: (2026)
FactorLLM: Factorizing Knowledge via Mixture of Experts for Large Language Models
by: Zhao, Zhongyu, et al.
Published: (2024)
by: Zhao, Zhongyu, et al.
Published: (2024)
Scaling Laws for Upcycling Mixture-of-Experts Language Models
by: Liew, Seng Pei, et al.
Published: (2025)
by: Liew, Seng Pei, et al.
Published: (2025)
HMoE: Heterogeneous Mixture of Experts for Language Modeling
by: Wang, An, et al.
Published: (2024)
by: Wang, An, 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)
Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models
by: Wang, Zihan, et al.
Published: (2025)
by: Wang, Zihan, et al.
Published: (2025)
Mixtures of SubExperts for Large Language Continual Learning
by: Kang, Haeyong
Published: (2025)
by: Kang, Haeyong
Published: (2025)
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)
Mixture of Heterogeneous Grouped Experts for Language Modeling
by: Ma, Zhicheng, et al.
Published: (2026)
by: Ma, Zhicheng, et al.
Published: (2026)
MoLAE: Mixture of Latent Experts for Parameter-Efficient Language Models
by: Liu, Zehua, et al.
Published: (2025)
by: Liu, Zehua, et al.
Published: (2025)
MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language Models
by: Tastan, Nurbek, et al.
Published: (2026)
by: Tastan, Nurbek, et al.
Published: (2026)
Domain-Specific Pruning of Large Mixture-of-Experts Models with Few-shot Demonstrations
by: Dong, Zican, et al.
Published: (2025)
by: Dong, Zican, et al.
Published: (2025)
Probing Semantic Routing in Large Mixture-of-Expert Models
by: Olson, Matthew Lyle, et al.
Published: (2025)
by: Olson, Matthew Lyle, et al.
Published: (2025)
CoSMoEs: Compact Sparse Mixture of Experts
by: Huber, Patrick, et al.
Published: (2025)
by: Huber, Patrick, et al.
Published: (2025)
LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models
by: Nguyen, Nam V., et al.
Published: (2024)
by: Nguyen, Nam V., 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)
Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training
by: Zhong, Zexuan, et al.
Published: (2024)
by: Zhong, Zexuan, et al.
Published: (2024)
Optimizing Pre-Training Data Mixtures with Mixtures of Data Expert Models
by: Belenki, Lior, et al.
Published: (2025)
by: Belenki, Lior, et al.
Published: (2025)
Mixture of Lookup Experts
by: Jie, Shibo, et al.
Published: (2025)
by: Jie, Shibo, et al.
Published: (2025)
Pruning and Distilling Mixture-of-Experts into Dense Language Models
by: Kim, Junhyuck, et al.
Published: (2026)
by: Kim, Junhyuck, et al.
Published: (2026)
OLMoE: Open Mixture-of-Experts Language Models
by: Muennighoff, Niklas, et al.
Published: (2024)
by: Muennighoff, Niklas, et al.
Published: (2024)
MLP Fusion: Towards Efficient Fine-tuning of Dense and Mixture-of-Experts Language Models
by: Ai, Mengting, et al.
Published: (2023)
by: Ai, Mengting, et al.
Published: (2023)
Towards Principled Design of Mixture-of-Experts Language Models under Memory and Inference Constraints
by: Liew, Seng Pei, et al.
Published: (2026)
by: Liew, Seng Pei, et al.
Published: (2026)
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)
Diversifying the Expert Knowledge for Task-Agnostic Pruning in Sparse Mixture-of-Experts
by: Zhang, Zeliang, et al.
Published: (2024)
by: Zhang, Zeliang, et al.
Published: (2024)
Every Expert Matters: Towards Effective Knowledge Distillation for Mixture-of-Experts Language Models
by: Kim, Gyeongman, et al.
Published: (2025)
by: Kim, Gyeongman, 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)
Optimal Sparsity of Mixture-of-Experts Language Models for Reasoning Tasks
by: Nakamura, Taishi, et al.
Published: (2025)
by: Nakamura, Taishi, et al.
Published: (2025)
Geometry-Preserving Aggregation for Mixture-of-Experts Embedding Models
by: Kachuee, Sajjad, et al.
Published: (2026)
by: Kachuee, Sajjad, et al.
Published: (2026)
Similar Items
-
ECHO-LLaMA: Efficient Caching for High-Performance LLaMA Training
by: Dialameh, Maryam, et al.
Published: (2025) -
FLOP-Efficient Training: Early Stopping Based on Test-Time Compute Awareness
by: Amer, Hossam, et al.
Published: (2026) -
LoRA-Drop: Temporal LoRA Decoding for Efficient LLM Inference
by: Rajabzadeh, Hossein, et al.
Published: (2026) -
EchoAtt: Attend, Copy, then Adjust for More Efficient Large Language Models
by: Rajabzadeh, Hossein, et al.
Published: (2024) -
QDyLoRA: Quantized Dynamic Low-Rank Adaptation for Efficient Large Language Model Tuning
by: Rajabzadeh, Hossein, et al.
Published: (2024)