Guardado en:
| Autores principales: | Gu, Yupu, Wei, Rongzhe, Zhu, Andy, Li, Pan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2602.10965 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
GRIP: Algorithm-Agnostic Machine Unlearning for Mixture-of-Experts via Geometric Router Constraints
por: Zhu, Andy, et al.
Publicado: (2026)
por: Zhu, Andy, et al.
Publicado: (2026)
Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging
por: Li, Lujun, et al.
Publicado: (2025)
por: Li, Lujun, et al.
Publicado: (2025)
ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing
por: Wang, Ziteng, et al.
Publicado: (2024)
por: Wang, Ziteng, et al.
Publicado: (2024)
Scalable Knowledge Editing for Mixture-of-Experts LLMs via Tensor-Structured Updates
por: Maksimov, Roman, et al.
Publicado: (2026)
por: Maksimov, Roman, et al.
Publicado: (2026)
Routing Manifold Alignment Improves Generalization of Mixture-of-Experts LLMs
por: Li, Zhongyang, et al.
Publicado: (2025)
por: Li, Zhongyang, et al.
Publicado: (2025)
MoBE: Mixture-of-Basis-Experts for Compressing MoE-based LLMs
por: Chen, Xiaodong, et al.
Publicado: (2025)
por: Chen, Xiaodong, et al.
Publicado: (2025)
Stable Routing for Mixture-of-Experts in Class-Incremental Learning
por: Guo, Zirui, et al.
Publicado: (2026)
por: Guo, Zirui, et al.
Publicado: (2026)
RouteHijack: Routing-Aware Attack on Mixture-of-Experts LLMs
por: Xu, Zhiyuan, et al.
Publicado: (2026)
por: Xu, Zhiyuan, et al.
Publicado: (2026)
CartesianMoE: Boosting Knowledge Sharing among Experts via Cartesian Product Routing in Mixture-of-Experts
por: Su, Zhenpeng, et al.
Publicado: (2024)
por: Su, Zhenpeng, et al.
Publicado: (2024)
Maximum Score Routing For Mixture-of-Experts
por: Dong, Bowen, et al.
Publicado: (2025)
por: Dong, Bowen, et al.
Publicado: (2025)
Efficiently Editing Mixture-of-Experts Models with Compressed Experts
por: He, Yifei, et al.
Publicado: (2025)
por: He, Yifei, et al.
Publicado: (2025)
ProbMoE: Differentiable Probabilistic Routing for Mixture-of-Experts
por: Zhao, Heng, et al.
Publicado: (2026)
por: Zhao, Heng, et al.
Publicado: (2026)
PreMoE: Proactive Inference for Efficient Mixture-of-Experts
por: Pei, Zehua, et al.
Publicado: (2025)
por: Pei, Zehua, et al.
Publicado: (2025)
Differentially Private Graph Diffusion with Applications in Personalized PageRanks
por: Wei, Rongzhe, et al.
Publicado: (2024)
por: Wei, Rongzhe, et al.
Publicado: (2024)
MoE++: Accelerating Mixture-of-Experts Methods with Zero-Computation Experts
por: Jin, Peng, et al.
Publicado: (2024)
por: Jin, Peng, et al.
Publicado: (2024)
MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing
por: Go, Seokjin, et al.
Publicado: (2025)
por: Go, Seokjin, et al.
Publicado: (2025)
PC-MoE: Memory-Efficient and Privacy-Preserving Collaborative Training for Mixture-of-Experts LLMs
por: Zhang, Ze Yu, et al.
Publicado: (2025)
por: Zhang, Ze Yu, et al.
Publicado: (2025)
Model Generalization on Text Attribute Graphs: Principles with Large Language Models
por: Wang, Haoyu, et al.
Publicado: (2025)
por: Wang, Haoyu, et al.
Publicado: (2025)
Sparse Models, Sparse Safety: Unsafe Routes in Mixture-of-Experts LLMs
por: Jiang, Yukun, et al.
Publicado: (2026)
por: Jiang, Yukun, et al.
Publicado: (2026)
Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference
por: Liu, Baihui, et al.
Publicado: (2026)
por: Liu, Baihui, et al.
Publicado: (2026)
Expert Routing for Communication-Efficient MoE via Finite Expert Banks
por: Salehi, Mohammad Reza Deylam, et al.
Publicado: (2026)
por: Salehi, Mohammad Reza Deylam, et al.
Publicado: (2026)
MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts
por: Xie, Zhitian, et al.
Publicado: (2024)
por: Xie, Zhitian, et al.
Publicado: (2024)
MoE-nD: Per-Layer Mixture-of-Experts Routing for Multi-Axis KV Cache Compression
por: Sun, Libo, et al.
Publicado: (2026)
por: Sun, Libo, et al.
Publicado: (2026)
Mixture Compressor for Mixture-of-Experts LLMs Gains More
por: Huang, Wei, et al.
Publicado: (2024)
por: Huang, Wei, et al.
Publicado: (2024)
Routing-Free Mixture-of-Experts
por: Liu, Yilun, et al.
Publicado: (2026)
por: Liu, Yilun, et al.
Publicado: (2026)
Multilingual Routing in Mixture-of-Experts
por: Bandarkar, Lucas, et al.
Publicado: (2025)
por: Bandarkar, Lucas, et al.
Publicado: (2025)
ResMoE: Space-efficient Compression of Mixture of Experts LLMs via Residual Restoration
por: Ai, Mengting, et al.
Publicado: (2025)
por: Ai, Mengting, et al.
Publicado: (2025)
Not All Models Suit Expert Offloading: On Local Routing Consistency of Mixture-of-Expert Models
por: Liang, Jingcong, et al.
Publicado: (2025)
por: Liang, Jingcong, et al.
Publicado: (2025)
When Are Experts Misrouted? Counterfactual Routing Analysis in Mixture-of-Experts Language Models
por: Yoon, Youngsik, et al.
Publicado: (2026)
por: Yoon, Youngsik, et al.
Publicado: (2026)
Input Domain Aware MoE: Decoupling Routing Decisions from Task Optimization in Mixture of Experts
por: Hua, Yongxiang, et al.
Publicado: (2025)
por: Hua, Yongxiang, et al.
Publicado: (2025)
Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts under State-Decomposable MDP
por: Pan, Yuxin, et al.
Publicado: (2025)
por: Pan, Yuxin, et al.
Publicado: (2025)
PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model
por: Liu, Yilun, et al.
Publicado: (2024)
por: Liu, Yilun, et al.
Publicado: (2024)
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models
por: Yin, Haoteng, et al.
Publicado: (2024)
por: Yin, Haoteng, et al.
Publicado: (2024)
CoMoE: Contrastive Representation for Mixture-of-Experts in Parameter-Efficient Fine-tuning
por: Feng, Jinyuan, et al.
Publicado: (2025)
por: Feng, Jinyuan, et al.
Publicado: (2025)
LAER-MoE: Load-Adaptive Expert Re-layout for Efficient Mixture-of-Experts Training
por: Liu, Xinyi, et al.
Publicado: (2026)
por: Liu, Xinyi, et al.
Publicado: (2026)
Parameter-Efficient Routed Fine-Tuning: Mixture-of-Experts Demands Mixture of Adaptation Modules
por: Liu, Yilun, et al.
Publicado: (2025)
por: Liu, Yilun, et al.
Publicado: (2025)
MoESD: Mixture of Experts Stable Diffusion to Mitigate Gender Bias
por: Wang, Guorun, et al.
Publicado: (2024)
por: Wang, Guorun, et al.
Publicado: (2024)
Horseshoe Mixtures-of-Experts (HS-MoE)
por: Polson, Nick, et al.
Publicado: (2026)
por: Polson, Nick, et al.
Publicado: (2026)
Geometric Mixture-of-Experts with Curvature-Guided Adaptive Routing for Graph Representation Learning
por: Cao, Haifang, et al.
Publicado: (2026)
por: Cao, Haifang, et al.
Publicado: (2026)
MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language Models
por: Tastan, Nurbek, et al.
Publicado: (2026)
por: Tastan, Nurbek, et al.
Publicado: (2026)
Ejemplares similares
-
GRIP: Algorithm-Agnostic Machine Unlearning for Mixture-of-Experts via Geometric Router Constraints
por: Zhu, Andy, et al.
Publicado: (2026) -
Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging
por: Li, Lujun, et al.
Publicado: (2025) -
ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing
por: Wang, Ziteng, et al.
Publicado: (2024) -
Scalable Knowledge Editing for Mixture-of-Experts LLMs via Tensor-Structured Updates
por: Maksimov, Roman, et al.
Publicado: (2026) -
Routing Manifold Alignment Improves Generalization of Mixture-of-Experts LLMs
por: Li, Zhongyang, et al.
Publicado: (2025)