Cover Image

Awakening Dormant Experts:Counterfactual Routing to Mitigate MoE Hallucinations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hu, Wentao, Zhai, Yanbo, Hu, Xiaohui, Zhao, Mingkuan, yu, Shanhong, Liu, Xue, Yu, Kaidong, Song, Shuangyong, Li, Xuelong
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Mosaic Pruning: A Hierarchical Framework for Generalizable Pruning of Mixture-of-Experts Models
by: Hu, Wentao, et al.
Published: (2025)

Awakening Dormant Users: Generative Recommendation with Counterfactual Functional Role Reasoning
by: Luo, Huishi, et al.
Published: (2026)

Prompt-Level Reward Specifications for Open-Ended Post-Training
by: Weng, Zijun, et al.
Published: (2026)

BadMoE: Backdooring Mixture-of-Experts LLMs via Optimizing Routing Triggers and Infecting Dormant Experts
by: Wang, Qingyue, et al.
Published: (2025)

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing
by: Min, Chengxi, et al.
Published: (2025)

Expert Routing for Communication-Efficient MoE via Finite Expert Banks
by: Salehi, Mohammad Reza Deylam, et al.
Published: (2026)

MoE Routing Testbed: Studying Expert Specialization and Routing Behavior at Small Scale
by: Falke, Tobias, et al.
Published: (2026)

BEAM: Binary Expert Activation Masking for Dynamic Routing in MoE
by: Wu, Juntong, et al.
Published: (2026)

MoE-Infinity: Efficient MoE Inference on Personal Machines with Sparsity-Aware Expert Cache
by: Xue, Leyang, et al.
Published: (2024)

EPS-MoE: Expert Pipeline Scheduler for Cost-Efficient MoE Inference
by: Qian, Yulei, et al.
Published: (2024)

Training Report of TeleChat3-MoE
by: Liu, Xinzhang, et al.
Published: (2025)

Grove MoE: Towards Efficient and Superior MoE LLMs with Adjugate Experts
by: Wu, Haoyuan, et al.
Published: (2025)

Polysemantic Experts, Monosemantic Paths: Routing as Control in MoEs
by: Ye, Charles, et al.
Published: (2026)

Harder Tasks Need More Experts: Dynamic Routing in MoE Models
by: Huang, Quzhe, et al.
Published: (2024)

ECG-MoE: Mixture-of-Expert Electrocardiogram Foundation Model
by: Xu, Yuhao, et al.
Published: (2026)

GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs
by: Deng, Jianing, et al.
Published: (2026)

MoE Pathfinder: Trajectory-driven Expert Pruning
by: Yang, Xican, et al.
Published: (2025)

LightCurve MoE: A Dynamic Sparse Routing Mixture-of-Experts Architecture for Efficient Stellar Light Curve Classification
by: Wang, Cunshi, et al.
Published: (2023)

Grouter: Decoupling Routing from Representation for Accelerated MoE Training
by: Xu, Yuqi, et al.
Published: (2026)

Expert-Token Resonance MoE: Bidirectional Routing with Efficiency Affinity-Driven Active Selection
by: Li, Jing, 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)

What Gets Activated: Uncovering Domain and Driver Experts in MoE Language Models
by: Hu, Guimin, et al.
Published: (2026)

LAR-MoE: Latent-Aligned Routing for Mixture of Experts in Robotic Imitation Learning
by: Rodriguez, Ariel, et al.
Published: (2026)

MoE-Loco: Mixture of Experts for Multitask Locomotion
by: Huang, Runhan, et al.
Published: (2025)

LLaDA-MoE: A Sparse MoE Diffusion Language Model
by: Zhu, Fengqi, et al.
Published: (2025)

MoE-LPR: Multilingual Extension of Large Language Models through Mixture-of-Experts with Language Priors Routing
by: Zhou, Hao, et al.
Published: (2024)

MoE-Sieve: Routing-Guided LoRA for Efficient MoE Fine-Tuning
by: Manzoni, Andrea
Published: (2026)

Synergistic Intra- and Cross-Layer Regularization Losses for MoE Expert Specialization
by: Hu, Rizhen, et al.
Published: (2026)

BrainStack: Neuro-MoE with Functionally Guided Expert Routing for EEG-Based Language Decoding
by: Zhao, Ziyi, et al.
Published: (2026)

Remoe: Towards Efficient and Low-Cost MoE Inference in Serverless Computing
by: Liu, Wentao, et al.
Published: (2025)

Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts
by: Li, Yunxin, et al.
Published: (2024)

OD-MoE: On-Demand Expert Loading for Cacheless Edge-Distributed MoE Inference
by: Wang, Liujianfu, et al.
Published: (2025)

A Dormant Captured Oort Cloud Comet Awakens: (18916) 2000 OG44
by: Chandler, Colin Orion, 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)

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training
by: Zheng, Size, et al.
Published: (2026)

Cross-Platform Fused MoE Dispatch in Triton: Portable Expert Routing Without CUDA
by: Mitra, Subhadip
Published: (2026)

GRACE-MoE: Grouping and Replication with Locality-Aware Routing for Efficient Distributed MoE Inference
by: Han, Yu, et al.
Published: (2025)

Advancing Expert Specialization for Better MoE
by: Guo, Hongcan, et al.
Published: (2025)

Horseshoe Mixtures-of-Experts (HS-MoE)
by: Polson, Nick, et al.
Published: (2026)

Improve LLM-as-a-Judge Ability as a General Ability
by: Yu, Jiachen, et al.
Published: (2025)