Expert Routing

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13 papers in the last four weeks, up 225% on the four weeks before. 0.1% of all new papers.

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Route by Kinematics, Act by Observation: Kinematics-Supervised Expert Routing in MoE-Augmented VLA
Jul 29, 2026Tianhang Yang, Yanze Zheng, Junjie Wang +3Robot Policy Learning Expert Routing
Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China · Pengcheng Lab, Shenzhen, China
Spend Experts Where You Are Unsure: Confidence-Adaptive Routing for Mixture-of-Experts LoRA
Jul 28, 2026Tom Saliencro, Rohan Desai, Priya Nair +2Parameter-Free Mixture-of-Experts Routing LLM Inference Acceleration
University of California, Irvine · University of Washington
OPERA: Offline Policy-guided Expert Routing and Adaptation for Universal Biomedical Image Analysis
Jul 27, 2026Zihan Li, Feiyang Liu, Dandan Shan +2Test-Time Adaptation Medical Image Analysis
University of Washington Seattle, USA · Delft University of Technology Delft, Netherlands · Xiamen University Xiamen, China
Hierarchical Copula-Gumbel-Top-\texorpdfstring{ $K$ }{K} Routing: Two-Sided Dependence Control for Frozen Mixture-of-Experts at Fixed Per-Token Routing Laws
Jul 25, 2026Richard Yi Da XuCopula Models Expert Load Balancing
Hong Kong Baptist University and TadReamk Limited
Beyond Independent Optimization: Compression, MoE Routing, and Quantization Interactions in Multimodal Edge Intelligence
Jul 23, 2026Jay Gor, Karm Dave, Akshita Abrol +3Efficient Multimodal Inference VLM Quantization
Nirma University · Singapore Institute of Technology, Singapore · Department of CE-AI and Big Data, Marwadi University
Multi-level context Modeling for consistent expert selection in Mixture-of-Experts
Jul 17, 2026Shuhan Huang, Naifan Zhang, Yuanbo Tang +2Mixture-of-Experts Language Models Expert Routing
Tsinghua Shenzhen International Graduate School, Tsinghua University · School of AI, The Chinese University of Hong Kong (Shenzhen)
From Global to Factor-Wise Expert Composition in Discrete Diffusion Models
Jul 13, 2026Haozhe Huang, Yudong Xu, Abhijoy Mandal +1Expert Routing Mixture-of-Experts Models
Department of Computer Science, University of Toronto · Vector Institute for Artificial Intelligence · Department of Mechanical & Industrial Engineering, University of Toronto +1
H-SAGE: Holistic Speaker-Aware Guided Experts for MoE-based Multi-Talker ASR
Jul 2, 2026Yujie Guo, Jiaming Zhou, Yuhang Jia +2Automatic Speech Recognition Expert Routing
TMCC, College of Computer Science, Nankai University, Tianjin, China
Focusing on What Matters: Saliency-Harnessing Accurate Routing for Diffusion MoE
Jun 25, 2026Haoyou Deng, Keyu Yan, Chaojie Mao +4Expert Routing Diffusion-Based Image Generation
Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology · Tongyi Lab, Alibaba Group
GeMoE: Gating Entropy is All You Need for Uncertainty-aware Adaptive Routing in MoE-based Large Vision-Language Models
Jun 24, 2026Chaoxiang Cai, Minghe Weng, Jie Li +4Efficient VLM Inference Large Vision-Language Models
School of Software Technology, Zhejiang University · College of Computer Science and Technology, Zhejiang University
SARA: Unlocking Multilingual Knowledge in Mixture-of-Experts via Semantically Anchored Routing Alignment
Jun 24, 2026Tianyu Dong, Yangyang Liu, Jiang Zhou +9Multilingual Language Models Sparse Mixture-of-Experts
TJUNLP Lab, School of Computer Science and Technology, Tianjin University, China · Alibaba Group, China
Optimal Scheduling in a Question-Answering Forum of Knowledge Workers
Jun 18, 2026Rohit Negi, Mustafa YilmazExpert Load Balancing Question Answering
Carnegie Mellon University
Task-Instructed Causal Routing of Vision Foundation Models for Multi-Task Learning
Jun 14, 2026Donghyun Han, Yuseok Bae, Jung Uk Kim +1Vision Foundation Model Adaptation Multi-Task Learning
Electronics and Telecommunications Research Institute (ETRI), Korea · Kyung Hee University, Korea · Chonnam National University, Korea
Sticky Routing: Training MoE Models for Memory-Efficient Inference
Jun 12, 2026Ali KayyamMixture-of-Experts Inference Memory-Efficient Inference
BrainChip Inc., Laguna Hills, CA
Redesign Mixture-of-Experts Routers with Manifold Power Iteration
Jun 10, 2026Songhao Wu, Ang Lv, Ruobing Xie +1Mixture-of-Experts Language Models Expert Routing
Gaoling School of Artificial Intelligence, Renmin University of China · Large Language Model Department, Tencent
PADD: Path-Aligned Decompression Distillation for Non-Router Teacher to Guide MoE Student Learning
Jun 9, 2026Xinyue Peng, Yi Qian, Jiaojiao Lin +2Mixture-of-Experts Language Models Expert Routing
Intel Corporation, China · Zhejiang University, China
STAR: Rethinking MoE Routing as Structure-Aware Subspace Learning
Jun 7, 2026Sumin Park, Noseong ParkSparse Mixture-of-Experts Expert Routing
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Value-and-Structure Alignment for Routing-Consistent Quantization of Mixture-of-Experts Models
Jun 4, 2026Hancheol Park, Geonho Lee, Tairen Piao +1LLM Quantization Mixture-of-Experts Quantization
Nota Inc., South Korea.
Expert-Aware Refusal Steering
Jun 2, 2026Anna C. Marbut, Daniel R. Olson, Travis J. WheelerMixture-of-Experts Language Models Language Model Steering
Department of Interdisciplinary Studies University of Montana Missoula, MT, USA · Department of Pharmacy Practice & Science University of Arizona Tucson, AZ, USA · European Bioinformatics Institute European Molecular Biology Laboratory Wellcome Genome Campus, Hinxton, United Kingdom
ProbMoE: Differentiable Probabilistic Routing for Mixture-of-Experts
Jun 1, 2026Heng Zhao, Zilei Shao, Guy Van den Broeck +1Sparse Mixture-of-Experts Expert Routing
Department of Computer Science, University of Virginia, Charlottesville, USA · Department of Computer Science, University of California, Los Angeles, Los Angeles, USA
PR2: Predictive Routing Replay for MoE-Based LLM Reinforcement Learning
May 29, 2026Daize Dong, Junlin Chen, Haolong Jia +9RL for Language Model Reasoning Expert Routing
♣Rutgers University · ♦AMD · ⋆MBZUAI
A Minimal Bifurcation Model of Load Imbalance in a Softmax Mixture-of-Experts Router
May 27, 2026O. M. KiselevDynamical Systems Expert Load Balancing
Innopolis University, Innopolis, Russia
AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting
May 24, 2026Rui Wang, Renhao Xue, Ray Razi +2Sparse Mixture-of-Experts Time Series Forecasting
Amazon Web Services
Safety-Oriented Routing Analysis of Mixtral MoE Under Benign and Harmful Prompts
May 22, 2026Md Nurul Absar SiddikyMixture-of-Experts Language Models Expert Routing
Department of Electrical and Computer Engineering University of Hawai’i at M¯anoa Honolulu, HI, USA
Can AI Guess What You Know? Performance Comparison of Large Language Models for Human Domain Knowledge Estimation From Communication Logs
May 21, 2026Ko Watanabe, Shoya IshimaruLLM Evaluation Expert Routing
DFKI, Kaiserslautern, Germany · Osaka Metropolitan University, Osaka, Japan
Mixture of Experts for Low-Resource LLMs
May 17, 2026Ori Bar Joseph, Smadar Arvatz, Noam Kayzer +2Mixture-of-Experts Language Models Expert Routing
Stable Routing for Mixture-of-Experts in Class-Incremental Learning
May 17, 2026Zirui Guo, Quan Cheng, Da-Wei Zhou +1Class-Incremental Learning Expert Routing
State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing, China · School of Artificial Intelligence, Nanjing University, Nanjing, China
When Does Sparse MoE Help in Vision? The Role of Backbone Compute Leverage in Sparse Routing
May 15, 2026Libo Sun, Po-wei Harn, Peixiong He +1Sparse Mixture-of-Experts Expert Routing
Department of Computer Science and Software Engineering Auburn University, Auburn, AL 36849, USA · Department of Information Management National Central University, Taoyuan 320317, Taiwan · Department of Computer Science and Software Engineering Auburn University
Sparse Mixture-of-Experts Routing in Visual Diffusion Transformers:Diagnosis, Boundary Calibration and Evolutionary Roadmap from Routing Collapse to Selective Deadlock
May 12, 2026Haiying ShaVideo Diffusion Models Diffusion Transformer
Independent Researcher
Routers Learn the Geometry of Their Experts: Geometric Coupling in Sparse Mixture-of-Experts
May 12, 2026Sagi Ahrac, Noya Hochwald, Mor GevaExpert Load Balancing Parameter-Free Mixture-of-Experts Routing
Blavatnik School of Computer Science and AI, Tel Aviv University

Jul 29, 2026, cs.ROJ/K move · Enter open · S save

Route by Kinematics, Act by Observation: Kinematics-Supervised Expert Routing in MoE-Augmented VLA

Tianhang Yang, Yanze Zheng, Junjie Wang, Wei-Bin Kou+2

Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China · Pengcheng Lab, Shenzhen, China

Robot Policy Learning Expert Routing VLMs for Robotics

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While MoE augments VLA via expert specialization, router suffers from ineffective expert routing owing to the kinematic heterogeneity of actions across manipulation tasks and, even worse, the unavailability of the kinematic signals at inference time. In this work, we first observe that most semantically distinct manipulation tasks reduce to multiple kinematic archetypes. Motivated by this finding, we propose Kinematics-supervised explicit routing (KinRT), a new paradigm that shifts from implicit, observation-driven expert routing to explicit, kinematics-guided expert dispatching. Specifically, we perform kinematic clustering on action trajectories into multiple kinematically coherent groups, whose IDs serve as ground truth to supervise the training of the router; at inference time, the router dispatches experts only using visual-language observations, without any reliance on action kinematics. KinRT actually introduces an asymmetric bridging mechanism that distills the task kinematics from the action space in training into the observation space at inference. In addition, to assess KinRT's cross-platform generalization, we build an economical, Do-It-Yourself robot (DIYRobot) platform from scratch using 3D-print technology (

<

2,000USD). Extensive experiments demonstrate KinRT's superiority over both dense and MoE-featured VLAs by more than 23.26% on RoboTwin benchmark and 20.27% on our introduced DIYRobot platform. Our code and DIYRobot platform will be open-sourced.

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