Ban&Pick: Ehancing Performance and Efficiency of MoE-LLMs via Smarter Routing
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Yuanteng, Wang, Peisong, Shao, Yuantian, Zeng, Nanxin, Xu, Chang, Cheng, Jian |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
EAC-MoE: Expert-Selection Aware Compressor for Mixture-of-Experts Large Language Models
by: Chen, Yuanteng, et al.
Published: (2025)
by: Chen, Yuanteng, et al.
Published: (2025)
Certain Head, Uncertain Tail: Expert-Sample for Test-Time Scaling in Fine-Grained MoE
by: Chen, Yuanteng, et al.
Published: (2026)
by: Chen, Yuanteng, et al.
Published: (2026)
IntraSlice: Towards High-Performance Structural Pruning with Block-Intra PCA for LLMs
by: Li, Meng, et al.
Published: (2026)
by: Li, Meng, et al.
Published: (2026)
Block Rotation is All You Need for MXFP4 Quantization
by: Shao, Yuantian, et al.
Published: (2025)
by: Shao, Yuantian, et al.
Published: (2025)
Defending MoE LLMs against Harmful Fine-Tuning via Safety Routing Alignment
by: Kim, Jaehan, et al.
Published: (2025)
by: Kim, Jaehan, et al.
Published: (2025)
BEAM: Binary Expert Activation Masking for Dynamic Routing in MoE
by: Wu, Juntong, et al.
Published: (2026)
by: Wu, Juntong, et al.
Published: (2026)
Grouter: Decoupling Routing from Representation for Accelerated MoE Training
by: Xu, Yuqi, et al.
Published: (2026)
by: Xu, Yuqi, et al.
Published: (2026)
MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning
by: Yang, Shu, et al.
Published: (2024)
by: Yang, Shu, et al.
Published: (2024)
D$^{2}$MoE: Dual Routing and Dynamic Scheduling for Efficient On-Device MoE-based LLM Serving
by: Wang, Haodong, et al.
Published: (2025)
by: Wang, Haodong, et al.
Published: (2025)
Awakening Dormant Experts:Counterfactual Routing to Mitigate MoE Hallucinations
by: Hu, Wentao, et al.
Published: (2026)
by: Hu, Wentao, et al.
Published: (2026)
Exploiting the Experts: Unauthorized Compression in MoE-LLMs
by: Neogi, Pinaki Prasad Guha, et al.
Published: (2025)
by: Neogi, Pinaki Prasad Guha, et al.
Published: (2025)
CoMoE: Collaborative Optimization of Expert Aggregation and Offloading for MoE-based LLMs at Edge
by: Li, Muqing, et al.
Published: (2025)
by: Li, Muqing, et al.
Published: (2025)
GazeFormer-MoE: Context-Aware Gaze Estimation via CLIP and MoE Transformer
by: Zhao, Xinyuan, et al.
Published: (2026)
by: Zhao, Xinyuan, et al.
Published: (2026)
Informed Routing in LLMs: Smarter Token-Level Computation for Faster Inference
by: Han, Chao, et al.
Published: (2025)
by: Han, Chao, et al.
Published: (2025)
KBVQ-MoE: KLT-guided SVD with Bias-Corrected Vector Quantization for MoE Large Language Models
by: Xu, Zukang, et al.
Published: (2026)
by: Xu, Zukang, et al.
Published: (2026)
Spectral Manifold Regularization for Stable and Modular Routing in Deep MoE Architectures
by: Delibasoglu, Ibrahim
Published: (2026)
by: Delibasoglu, Ibrahim
Published: (2026)
ShardMemo: Masked MoE Routing for Sharded Agentic LLM Memory
by: Zhao, Yang, et al.
Published: (2026)
by: Zhao, Yang, et al.
Published: (2026)
PR2: Predictive Routing Replay for MoE-Based LLM Reinforcement Learning
by: Dong, Daize, et al.
Published: (2026)
by: Dong, Daize, et al.
Published: (2026)
MoE-PHDS: One MoE checkpoint for flexible runtime sparsity
by: Hannah, Lauren. A, et al.
Published: (2025)
by: Hannah, Lauren. A, et al.
Published: (2025)
Improving MoE Compute Efficiency by Composing Weight and Data Sparsity
by: Kilian, Maciej, et al.
Published: (2026)
by: Kilian, Maciej, et al.
Published: (2026)
LLaDA-MoE: A Sparse MoE Diffusion Language Model
by: Zhu, Fengqi, et al.
Published: (2025)
by: Zhu, Fengqi, et al.
Published: (2025)
MoEITS: A Green AI approach for simplifying MoE-LLMs
by: Balderas, Luis, et al.
Published: (2026)
by: Balderas, Luis, et al.
Published: (2026)
Unveiling and Consulting Core Experts in Retrieval-Augmented MoE-based LLMs
by: Zhou, Xin, et al.
Published: (2024)
by: Zhou, Xin, et al.
Published: (2024)
GMoE: Empowering LLMs Fine-Tuning via MoE Graph Collaboration
by: Bai, Ting, et al.
Published: (2024)
by: Bai, Ting, et al.
Published: (2024)
GW-MoE: Resolving Uncertainty in MoE Router with Global Workspace Theory
by: Wu, Haoze, et al.
Published: (2024)
by: Wu, Haoze, et al.
Published: (2024)
CoGR-MoE: Concept-Guided Expert Routing with Consistent Selection and Flexible Reasoning for Visual Question Answering
by: Zeng, Xiyin, et al.
Published: (2026)
by: Zeng, Xiyin, et al.
Published: (2026)
Input Domain Aware MoE: Decoupling Routing Decisions from Task Optimization in Mixture of Experts
by: Hua, Yongxiang, et al.
Published: (2025)
by: Hua, Yongxiang, et al.
Published: (2025)
Safety-Oriented Routing Analysis of Mixtral MoE Under Benign and Harmful Prompts
by: Siddiky, Md Nurul Absar
Published: (2026)
by: Siddiky, Md Nurul Absar
Published: (2026)
Unveiling Language Routing Isolation in Multilingual MoE Models for Interpretable Subnetwork Adaptation
by: Zheng, Kening, et al.
Published: (2026)
by: Zheng, Kening, et al.
Published: (2026)
SonicMoE: Accelerating MoE with IO and Tile-aware Optimizations
by: Guo, Wentao, et al.
Published: (2025)
by: Guo, Wentao, et al.
Published: (2025)
BrainStack: Neuro-MoE with Functionally Guided Expert Routing for EEG-Based Language Decoding
by: Zhao, Ziyi, et al.
Published: (2026)
by: Zhao, Ziyi, et al.
Published: (2026)
ProbMoE: Differentiable Probabilistic Routing for Mixture-of-Experts
by: Zhao, Heng, et al.
Published: (2026)
by: Zhao, Heng, et al.
Published: (2026)
Sigma-MoE-Tiny Technical Report
by: Hu, Qingguo, et al.
Published: (2025)
by: Hu, Qingguo, et al.
Published: (2025)
Leave It to the Experts: Detecting Knowledge Distillation via MoE Expert Signatures
by: Li, Pingzhi, et al.
Published: (2025)
by: Li, Pingzhi, et al.
Published: (2025)
GRIN: GRadient-INformed MoE
by: Liu, Liyuan, et al.
Published: (2024)
by: Liu, Liyuan, et al.
Published: (2024)
SecMoE: Communication-Efficient Secure MoE Inference via Select-Then-Compute
by: Shen, Bowen, et al.
Published: (2026)
by: Shen, Bowen, et al.
Published: (2026)
Enhancing Online Recruitment with Category-Aware MoE and LLM-based Data Augmentation
by: Chen, Minping, et al.
Published: (2026)
by: Chen, Minping, et al.
Published: (2026)
MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design
by: Duanmu, Haojie, et al.
Published: (2025)
by: Duanmu, Haojie, et al.
Published: (2025)
DTop-p MoE: Sparsity-Controlled Dynamic Top-p MoE for Foundation Model Pre-training
by: Jin, Can, et al.
Published: (2025)
by: Jin, Can, et al.
Published: (2025)
Polysemantic Experts, Monosemantic Paths: Routing as Control in MoEs
by: Ye, Charles, et al.
Published: (2026)
by: Ye, Charles, et al.
Published: (2026)
Similar Items
-
EAC-MoE: Expert-Selection Aware Compressor for Mixture-of-Experts Large Language Models
by: Chen, Yuanteng, et al.
Published: (2025) -
Certain Head, Uncertain Tail: Expert-Sample for Test-Time Scaling in Fine-Grained MoE
by: Chen, Yuanteng, et al.
Published: (2026) -
IntraSlice: Towards High-Performance Structural Pruning with Block-Intra PCA for LLMs
by: Li, Meng, et al.
Published: (2026) -
Block Rotation is All You Need for MXFP4 Quantization
by: Shao, Yuantian, et al.
Published: (2025) -
Defending MoE LLMs against Harmful Fine-Tuning via Safety Routing Alignment
by: Kim, Jaehan, et al.
Published: (2025)