Image de couverture de livre

RotMoLE: Enhancing Mixture of Low-Rank Experts through Rotational Gating Mechanism

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Sun, Mengyang, Dou, Maochuan, Feng, Tao, Zhang, Dan, Wang, Yihao, Liu, Junpeng, Zhu, Yifan, Tang, Jie
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
par: Sun, Mengyang, et autres
Publié: (2025)

MoLE: Enhancing Human-centric Text-to-image Diffusion via Mixture of Low-rank Experts
par: Zhu, Jie, et autres
Publié: (2024)

GM-MoE: Low-Light Enhancement with Gated-Mechanism Mixture-of-Experts
par: Liao, Minwen, et autres
Publié: (2025)

AdaMoLE: Fine-Tuning Large Language Models with Adaptive Mixture of Low-Rank Adaptation Experts
par: Liu, Zefang, et autres
Publié: (2024)

DynMoLE: Boosting Mixture of LoRA Experts Fine-Tuning with a Hybrid Routing Mechanism
par: Li, Dengchun, et autres
Publié: (2025)

LeMoLE: LLM-Enhanced Mixture of Linear Experts for Time Series Forecasting
par: Zhang, Lingzheng, et autres
Publié: (2024)

MoBiLE: Efficient Mixture-of-Experts Inference on Consumer GPU with Mixture of Big Little Experts
par: Zhao, Yushu, et autres
Publié: (2025)

MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition
par: Yang, Cheng, et autres
Publié: (2024)

MoR: Mixture of Ranks for Low-Rank Adaptation Tuning
par: Tang, Chuanyu, et autres
Publié: (2024)

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation
par: Xiao, Jinqi, et autres
Publié: (2025)

LD-MoLE: Learnable Dynamic Routing for Mixture of LoRA Experts
par: Zhuang, Yuan, et autres
Publié: (2025)

LightMoE: Reducing Mixture-of-Experts Redundancy through Expert Replacing
par: Hao, Jiawei, et autres
Publié: (2026)

MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
par: Zhang, Dacao, et autres
Publié: (2025)

LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs
par: Chen, Shaoxiang, et autres
Publié: (2024)

TAG-MoE: Task-Aware Gating for Unified Generative Mixture-of-Experts
par: Xu, Yu, et autres
Publié: (2026)

GaVaMoE: Gaussian-Variational Gated Mixture of Experts for Explainable Recommendation
par: Tang, Fei, et autres
Publié: (2024)

MINGLE: Mixture of Null-Space Gated Low-Rank Experts for Test-Time Continual Model Merging
par: Qiu, Zihuan, et autres
Publié: (2025)

Low-Rank Mixture-of-Experts for Continual Medical Image Segmentation
par: Chen, Qian, et autres
Publié: (2024)

Multi-Task Dense Prediction via Mixture of Low-Rank Experts
par: Yang, Yuqi, et autres
Publié: (2024)

L-MoE: End-to-End Training of a Lightweight Mixture of Low-Rank Adaptation Experts
par: Ji, Shihao, et autres
Publié: (2025)

TeleGate: Whole-Body Humanoid Teleoperation via Gated Expert Selection with Motion Prior
par: Li, Jie, et autres
Publié: (2026)

PM-MOE: Mixture of Experts on Private Model Parameters for Personalized Federated Learning
par: Feng, Yu, et autres
Publié: (2025)

SMILE: Zero-Shot Sparse Mixture of Low-Rank Experts Construction From Pre-Trained Foundation Models
par: Tang, Anke, et autres
Publié: (2024)

MoPEQ: Mixture of Mixed Precision Quantized Experts
par: Chitty-Venkata, Krishna Teja, et autres
Publié: (2025)

Mixture of Experts for Low-Resource LLMs
par: Joseph, Ori Bar, et autres
Publié: (2026)

SEER-MoE: Sparse Expert Efficiency through Regularization for Mixture-of-Experts
par: Muzio, Alexandre, et autres
Publié: (2024)

WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting
par: Wu, Shunyu, et autres
Publié: (2026)

Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
par: Zhao, Ziyu, et autres
Publié: (2025)

MoE++: Accelerating Mixture-of-Experts Methods with Zero-Computation Experts
par: Jin, Peng, et autres
Publié: (2024)

Confucianism and employee treatment: Evidence from China
par: Xixiong Xu, et autres
Publié: (2024)

VA-MoE: Variables-Adaptive Mixture of Experts for Incremental Weather Forecasting
par: Chen, Hao, et autres
Publié: (2024)

One-for-All Does Not Work! Enhancing Vulnerability Detection by Mixture-of-Experts (MoE)
par: Yang, Xu, et autres
Publié: (2025)

FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of Experts
par: Liu, Ziqi
Publié: (2025)

Multimodal Mixture of Low-Rank Experts for Sentiment Analysis and Emotion Recognition
par: Zhang, Shuo, et autres
Publié: (2025)

Mixture of Low-Rank Adapter Experts in Generalizable Audio Deepfake Detection
par: Laakkonen, Janne, et autres
Publié: (2025)

Bandwidth-Efficient Adaptive Mixture-of-Experts via Low-Rank Compensation
par: Liu, Zhenyu, et autres
Publié: (2025)

Adaptive Mixture of Low-Rank Experts for Robust Audio Spoofing Detection
par: Chen, Qixian, et autres
Publié: (2025)

OrdMoE: Preference Alignment via Hierarchical Expert Group Ranking in Multimodal Mixture-of-Experts LLMs
par: Gao, Yuting, et autres
Publié: (2025)

MoE-Loco: Mixture of Experts for Multitask Locomotion
par: Huang, Runhan, et autres
Publié: (2025)

ViMoE: An Empirical Study of Designing Vision Mixture-of-Experts
par: Han, Xumeng, et autres
Publié: (2024)