:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Pan, Dong, Li, Bingtao, Zheng, Yongsheng, Ma, Jiren, Fei, Victor
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2602.08019
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications
by: Mu, Siyuan, et al.
Published: (2025)

Modeling Expert Interactions in Sparse Mixture of Experts via Graph Structures
by: Nguyen-Nhat, Minh-Khoi, et al.
Published: (2025)

Exploring Expert Specialization through Unsupervised Training in Sparse Mixture of Experts
by: Nikolic, Strahinja, et al.
Published: (2025)

Dense Backpropagation Improves Training for Sparse Mixture-of-Experts
by: Panda, Ashwinee, et al.
Published: (2025)

SMILE: Zero-Shot Sparse Mixture of Low-Rank Experts Construction From Pre-Trained Foundation Models
by: Tang, Anke, et al.
Published: (2024)

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference
by: Zhao, Yushu, et al.
Published: (2025)

GRIP: Algorithm-Agnostic Machine Unlearning for Mixture-of-Experts via Geometric Router Constraints
by: Zhu, Andy, et al.
Published: (2026)

Eradicating Negative Transfer in Multi-Physics Foundation Models via Sparse Mixture-of-Experts Routing
by: Sharma, Ellwil, et al.
Published: (2026)

Soft-to-Hard Routing in Sparse Mixture-of-Experts Models
by: Rastegar, Reza
Published: (2026)

Sparse Models, Sparse Safety: Unsafe Routes in Mixture-of-Experts LLMs
by: Jiang, Yukun, et al.
Published: (2026)

Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models
by: Pan, Bowen, et al.
Published: (2024)

From Sparse to Soft Mixtures of Experts
by: Puigcerver, Joan, et al.
Published: (2023)

HodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts
by: Zhong, Tao, et al.
Published: (2026)

Revisiting Incremental Stochastic Majorization-Minimization Algorithms with Applications to Mixture of Experts
by: Tran, TrungKhang, et al.
Published: (2026)

dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis
by: Xie, Luyuan, et al.
Published: (2025)

Unified Class and Domain Incremental Learning with Mixture of Experts for Indoor Localization
by: Singampalli, Akhil, et al.
Published: (2025)

A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
by: Sun, Mengyang, et al.
Published: (2025)

UniPool: A Globally Shared Expert Pool for Mixture-of-Experts
by: Huang, Minbin, et al.
Published: (2026)

The Illusion of Specialization: Unveiling the Domain-Invariant "Standing Committee" in Mixture-of-Experts Models
by: Wang, Yan, et al.
Published: (2026)

Mixture-of-Experts Meets In-Context Reinforcement Learning
by: Wu, Wenhao, et al.
Published: (2025)

Mixture of Raytraced Experts
by: Perin, Andrea, et al.
Published: (2025)

Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
by: Shi, Xiaoming, et al.
Published: (2024)

Wavelet Mixture of Experts for Time Series Forecasting
by: Zhou, Zheng, et al.
Published: (2025)

Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization
by: Nakamura, Taishi, et al.
Published: (2025)

Routing-Free Mixture-of-Experts
by: Liu, Yilun, et al.
Published: (2026)

Mixture of Experts in a Mixture of RL settings
by: Willi, Timon, et al.
Published: (2024)

Speculating Experts Accelerates Inference for Mixture-of-Experts
by: Madan, Vivan, et al.
Published: (2026)

MoFE-Time: Mixture of Frequency Domain Experts for Time-Series Forecasting Models
by: Liu, Yiwen, et al.
Published: (2025)

MIDG: Mixture of Invariant Experts with knowledge injection for Domain Generalization in Multimodal Sentiment Analysis
by: Li, Yangle, et al.
Published: (2025)

HELLoRA: Hot Experts Layer-Level Low-Rank Adaptation for Mixture-of-Experts Models
by: Wei, Jia, et al.
Published: (2026)

Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey
by: Xu, Minrui, et al.
Published: (2024)

Klotski: Efficient Mixture-of-Expert Inference via Expert-Aware Multi-Batch Pipeline
by: Fang, Zhiyuan, et al.
Published: (2025)

TT-LoRA MoE: Unifying Parameter-Efficient Fine-Tuning and Sparse Mixture-of-Experts
by: Kunwar, Pradip, et al.
Published: (2025)

MC#: Mixture Compressor for Mixture-of-Experts Large Models
by: Huang, Wei, et al.
Published: (2025)

MoNDE: Mixture of Near-Data Experts for Large-Scale Sparse Models
by: Kim, Taehyun, et al.
Published: (2024)

MLPMoE: Zero-Shot Architectural Metamorphosis of Dense LLM MLPs into Static Mixture-of-Experts
by: Novikov, Ivan
Published: (2025)

Mixture of Diverse Size Experts
by: Sun, Manxi, et al.
Published: (2024)

Sparsity and Superposition in Mixture of Experts
by: Chaudhari, Marmik, et al.
Published: (2025)

Mixture of Concept Bottleneck Experts
by: De Santis, Francesco, et al.
Published: (2026)

Mixture of A Million Experts
by: He, Xu Owen
Published: (2024)