Patch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation
Fuente:
arXiv
Saved in:
| Main Authors: | Adame, Diego, Vazquez, Fabian, Nunez, Jose A., Li, Huimin, Yang, Jinghao, Enriquez, Erik, Kim, DongChul, Tang, Haoteng, Fu, Bin, Gu, Pengfei |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Integrating Multi-scale and Multi-filtration Topological Features for Medical Image Classification
by: Gu, Pengfei, et al.
Published: (2025)
by: Gu, Pengfei, et al.
Published: (2025)
Topo-VM-UNetV2: Encoding Topology into Vision Mamba UNet for Polyp Segmentation
by: Adame, Diego, et al.
Published: (2025)
by: Adame, Diego, et al.
Published: (2025)
Learning with Geometric Priors in U-Net Variants for Polyp Segmentation
by: Vazquez, Fabian, et al.
Published: (2026)
by: Vazquez, Fabian, et al.
Published: (2026)
Adapting a Segmentation Foundation Model for Medical Image Classification
by: Gu, Pengfei, et al.
Published: (2025)
by: Gu, Pengfei, et al.
Published: (2025)
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts
by: Pióro, Maciej, et al.
Published: (2024)
by: Pióro, Maciej, et al.
Published: (2024)
Adaptive Normalization Mamba with Multi Scale Trend Decomposition and Patch MoE Encoding
by: Jeon, MinCheol
Published: (2025)
by: Jeon, MinCheol
Published: (2025)
SwIPE: Efficient and Robust Medical Image Segmentation with Implicit Patch Embeddings
by: Zhang, Yejia, et al.
Published: (2023)
by: Zhang, Yejia, et al.
Published: (2023)
Horseshoe Mixtures-of-Experts (HS-MoE)
by: Polson, Nick, et al.
Published: (2026)
by: Polson, Nick, et al.
Published: (2026)
Semi-MoE: Mixture-of-Experts meets Semi-Supervised Histopathology Segmentation
by: Vu, Nguyen Lan Vi, et al.
Published: (2025)
by: Vu, Nguyen Lan Vi, et al.
Published: (2025)
$\infty$-MoE: Generalizing Mixture of Experts to Infinite Experts
by: Takashiro, Shota, et al.
Published: (2026)
by: Takashiro, Shota, et al.
Published: (2026)
MH-MoE: Multi-Head Mixture-of-Experts
by: Huang, Shaohan, et al.
Published: (2024)
by: Huang, Shaohan, et al.
Published: (2024)
MoE-Loco: Mixture of Experts for Multitask Locomotion
by: Huang, Runhan, et al.
Published: (2025)
by: Huang, Runhan, et al.
Published: (2025)
Elastic MoE: Unlocking the Inference-Time Scalability of Mixture-of-Experts
by: Gu, Naibin, et al.
Published: (2025)
by: Gu, Naibin, et al.
Published: (2025)
Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging
by: Li, Lujun, et al.
Published: (2025)
by: Li, Lujun, et al.
Published: (2025)
MoE++: Accelerating Mixture-of-Experts Methods with Zero-Computation Experts
by: Jin, Peng, et al.
Published: (2024)
by: Jin, Peng, et al.
Published: (2024)
MoBE: Mixture-of-Basis-Experts for Compressing MoE-based LLMs
by: Chen, Xiaodong, et al.
Published: (2025)
by: Chen, Xiaodong, et al.
Published: (2025)
LAER-MoE: Load-Adaptive Expert Re-layout for Efficient Mixture-of-Experts Training
by: Liu, Xinyi, et al.
Published: (2026)
by: Liu, Xinyi, et al.
Published: (2026)
X-MoE: Enabling Scalable Training for Emerging Mixture-of-Experts Architectures on HPC Platforms
by: Yuan, Yueming, et al.
Published: (2025)
by: Yuan, Yueming, et al.
Published: (2025)
Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language Models
by: Jiang, Songtao, et al.
Published: (2024)
by: Jiang, Songtao, et al.
Published: (2024)
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
by: Lin, Bin, et al.
Published: (2024)
by: Lin, Bin, et al.
Published: (2024)
White Light Specular Reflection Data Augmentation for Deep Learning Polyp Detection
by: Nuñez, Jose Angel, et al.
Published: (2025)
by: Nuñez, Jose Angel, et al.
Published: (2025)
Mixture of Experts (MoE): A Big Data Perspective
by: Gan, Wensheng, et al.
Published: (2025)
by: Gan, Wensheng, et al.
Published: (2025)
SDG-MoE: Signed Debate Graph Mixture-of-Experts
by: Kulibaba, Stepan, et al.
Published: (2026)
by: Kulibaba, Stepan, et al.
Published: (2026)
ECG-MoE: Mixture-of-Expert Electrocardiogram Foundation Model
by: Xu, Yuhao, et al.
Published: (2026)
by: Xu, Yuhao, et al.
Published: (2026)
MoE-GS: Mixture of Experts for Dynamic Gaussian Splatting
by: Jin, In-Hwan, et al.
Published: (2025)
by: Jin, In-Hwan, et al.
Published: (2025)
DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts
by: Feng, Jiarui, et al.
Published: (2026)
by: Feng, Jiarui, et al.
Published: (2026)
DA-MoE: Towards Dynamic Expert Allocation for Mixture-of-Experts Models
by: Aghdam, Maryam Akhavan, et al.
Published: (2024)
by: Aghdam, Maryam Akhavan, et al.
Published: (2024)
SEER-MoE: Sparse Expert Efficiency through Regularization for Mixture-of-Experts
by: Muzio, Alexandre, et al.
Published: (2024)
by: Muzio, Alexandre, et al.
Published: (2024)
MoME: Mixture of Visual Language Medical Experts for Medical Imaging Segmentation
by: Rezvani, Arghavan, et al.
Published: (2025)
by: Rezvani, Arghavan, et al.
Published: (2025)
Seg-MoE: Multi-Resolution Segment-wise Mixture-of-Experts for Time Series Forecasting Transformers
by: Ortigossa, Evandro S., et al.
Published: (2026)
by: Ortigossa, Evandro S., et al.
Published: (2026)
PWC-MoE: Privacy-Aware Wireless Collaborative Mixture of Experts
by: Su, Yang, et al.
Published: (2025)
by: Su, Yang, et al.
Published: (2025)
Hexa-MoE: Efficient and Heterogeneous-aware Training for Mixture-of-Experts
by: Luo, Shuqing, et al.
Published: (2024)
by: Luo, Shuqing, et al.
Published: (2024)
Linear-MoE: Linear Sequence Modeling Meets Mixture-of-Experts
by: Sun, Weigao, et al.
Published: (2025)
by: Sun, Weigao, et al.
Published: (2025)
Astro-MoE: Mixture of Experts for Multiband Astronomical Time Series
by: Cádiz-Leyton, Martina, et al.
Published: (2025)
by: Cádiz-Leyton, Martina, et al.
Published: (2025)
Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts
by: Li, Yunxin, et al.
Published: (2024)
by: Li, Yunxin, et al.
Published: (2024)
Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity
by: Tang, Yehui, et al.
Published: (2025)
by: Tang, Yehui, et al.
Published: (2025)
CP-MoE: Consistency-Preserving Mixture-of-Experts for Continual Learning
by: Liu, Yang, et al.
Published: (2026)
by: Liu, Yang, et al.
Published: (2026)
BadPatches: Routing-aware Backdoor Attacks on Vision Mixture of Experts
by: Chan, Cedric, et al.
Published: (2025)
by: Chan, Cedric, et al.
Published: (2025)
Point-MoE: Large-Scale Multi-Dataset Training with Mixture-of-Experts for 3D Semantic Segmentation
by: Chen, Xuweiyi, et al.
Published: (2025)
by: Chen, Xuweiyi, et al.
Published: (2025)
MoECLIP: Patch-Specialized Experts for Zero-shot Anomaly Detection
by: Park, Jun Yeong, et al.
Published: (2026)
by: Park, Jun Yeong, et al.
Published: (2026)
Similar Items
-
Integrating Multi-scale and Multi-filtration Topological Features for Medical Image Classification
by: Gu, Pengfei, et al.
Published: (2025) -
Topo-VM-UNetV2: Encoding Topology into Vision Mamba UNet for Polyp Segmentation
by: Adame, Diego, et al.
Published: (2025) -
Learning with Geometric Priors in U-Net Variants for Polyp Segmentation
by: Vazquez, Fabian, et al.
Published: (2026) -
Adapting a Segmentation Foundation Model for Medical Image Classification
by: Gu, Pengfei, et al.
Published: (2025) -
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts
by: Pióro, Maciej, et al.
Published: (2024)