Routers in Vision Mixture of Experts: An Empirical Study
Fuente:
arXiv
Guardado en:
| Autores principales: | Liu, Tianlin, Blondel, Mathieu, Riquelme, Carlos, Puigcerver, Joan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
From Sparse to Soft Mixtures of Experts
por: Puigcerver, Joan, et al.
Publicado: (2023)
por: Puigcerver, Joan, et al.
Publicado: (2023)
Parameter-Efficient Quantized Mixture-of-Experts Meets Vision-Language Instruction Tuning for Semiconductor Electron Micrograph Analysis
por: Srinivas, Sakhinana Sagar, et al.
Publicado: (2024)
por: Srinivas, Sakhinana Sagar, et al.
Publicado: (2024)
BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma
por: Yang, Junlin, et al.
Publicado: (2026)
por: Yang, Junlin, et al.
Publicado: (2026)
Co-Supervised Learning: Improving Weak-to-Strong Generalization with Hierarchical Mixture of Experts
por: Liu, Yuejiang, et al.
Publicado: (2024)
por: Liu, Yuejiang, et al.
Publicado: (2024)
Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts
por: Yuan, Yike, et al.
Publicado: (2025)
por: Yuan, Yike, et al.
Publicado: (2025)
Adaptive Shared Experts with LoRA-Based Mixture of Experts for Multi-Task Learning
por: Yang, Minghao, et al.
Publicado: (2025)
por: Yang, Minghao, et al.
Publicado: (2025)
Mixture of Nested Experts: Adaptive Processing of Visual Tokens
por: Jain, Gagan, et al.
Publicado: (2024)
por: Jain, Gagan, et al.
Publicado: (2024)
MoQE: Improve Quantization Model performance via Mixture of Quantization Experts
por: Zhang, Jinhao, et al.
Publicado: (2025)
por: Zhang, Jinhao, et al.
Publicado: (2025)
PA-Net: Precipitation-Adaptive Mixture-of-Experts for Long-Tail Rainfall Nowcasting
por: Xiao, Xinyu, et al.
Publicado: (2026)
por: Xiao, Xinyu, et al.
Publicado: (2026)
Universal Multi-Domain Translation via Diffusion Routers
por: Kieu, Duc, et al.
Publicado: (2025)
por: Kieu, Duc, et al.
Publicado: (2025)
Prismer: A Vision-Language Model with Multi-Task Experts
por: Liu, Shikun, et al.
Publicado: (2023)
por: Liu, Shikun, et al.
Publicado: (2023)
MoSE: Skill-by-Skill Mixture-of-Experts Learning for Embodied Autonomous Machines
por: Xu, Lu, et al.
Publicado: (2025)
por: Xu, Lu, et al.
Publicado: (2025)
I2MoE: Interpretable Multimodal Interaction-aware Mixture-of-Experts
por: Xin, Jiayi, et al.
Publicado: (2025)
por: Xin, Jiayi, et al.
Publicado: (2025)
MoEIoU: Rethinking Bounding-Box Regression as a Mixture of Experts
por: Edula, Vinay, et al.
Publicado: (2026)
por: Edula, Vinay, et al.
Publicado: (2026)
CP-MoE: Consistency-Preserving Mixture-of-Experts for Continual Learning
por: Liu, Yang, et al.
Publicado: (2026)
por: Liu, Yang, et al.
Publicado: (2026)
MoPE: Mixture of Prompt Experts for Parameter-Efficient and Scalable Multimodal Fusion
por: Jiang, Ruixiang, et al.
Publicado: (2024)
por: Jiang, Ruixiang, et al.
Publicado: (2024)
MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
por: Teo, Rachel S. Y., et al.
Publicado: (2024)
por: Teo, Rachel S. Y., et al.
Publicado: (2024)
MoLEx: Mixture of Layer Experts for Finetuning with Sparse Upcycling
por: Teo, Rachel S. Y., et al.
Publicado: (2025)
por: Teo, Rachel S. Y., et al.
Publicado: (2025)
MoLE: Enhancing Human-centric Text-to-image Diffusion via Mixture of Low-rank Experts
por: Zhu, Jie, et al.
Publicado: (2024)
por: Zhu, Jie, et al.
Publicado: (2024)
SPADE: Spatial Transcriptomics and Pathology Alignment Using a Mixture of Data Experts for an Expressive Latent Space
por: Redekop, Ekaterina, et al.
Publicado: (2025)
por: Redekop, Ekaterina, et al.
Publicado: (2025)
GC-MoE: Genomics-Guided Cell-Type-Specific Mixture of Experts for Histology-Based Single-Cell Spatial Transcriptomics
por: Shiku, Kaito, et al.
Publicado: (2026)
por: Shiku, Kaito, et al.
Publicado: (2026)
Multi-level Mixture of Experts for Multimodal Entity Linking
por: Hu, Zhiwei, et al.
Publicado: (2025)
por: Hu, Zhiwei, et al.
Publicado: (2025)
Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies
por: Drokin, Ivan
Publicado: (2024)
por: Drokin, Ivan
Publicado: (2024)
From Image to Video: An Empirical Study of Diffusion Representations
por: Vélez, Pedro, et al.
Publicado: (2025)
por: Vélez, Pedro, et al.
Publicado: (2025)
Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imaging
por: Yang, Yuzhe, et al.
Publicado: (2024)
por: Yang, Yuzhe, et al.
Publicado: (2024)
An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Encoders
por: Lowe, Scott C., et al.
Publicado: (2024)
por: Lowe, Scott C., et al.
Publicado: (2024)
Machine Unlearning in the Era of Quantum Machine Learning: An Empirical Study
por: Crivoi, Carla, et al.
Publicado: (2025)
por: Crivoi, Carla, et al.
Publicado: (2025)
MouSi: Poly-Visual-Expert Vision-Language Models
por: Fan, Xiaoran, et al.
Publicado: (2024)
por: Fan, Xiaoran, et al.
Publicado: (2024)
Double-Stage Feature-Level Clustering-Based Mixture of Experts Framework
por: Badjie, Bakary, et al.
Publicado: (2025)
por: Badjie, Bakary, et al.
Publicado: (2025)
XAI for Skin Cancer Detection with Prototypes and Non-Expert Supervision
por: Correia, Miguel, et al.
Publicado: (2024)
por: Correia, Miguel, et al.
Publicado: (2024)
A Large-Scale Empirical Study on Improving the Fairness of Image Classification Models
por: Yang, Junjie, et al.
Publicado: (2024)
por: Yang, Junjie, et al.
Publicado: (2024)
SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of Experts
por: Zhou, Gengze, et al.
Publicado: (2024)
por: Zhou, Gengze, et al.
Publicado: (2024)
MEGAN: Mixture of Experts for Robust Uncertainty Estimation in Endoscopy Videos
por: Agbelese, Damola, et al.
Publicado: (2025)
por: Agbelese, Damola, et al.
Publicado: (2025)
EvidenceMoE: A Physics-Guided Mixture-of-Experts with Evidential Critics for Advancing Fluorescence Light Detection and Ranging in Scattering Media
por: Erbas, Ismail, et al.
Publicado: (2025)
por: Erbas, Ismail, et al.
Publicado: (2025)
Object-Centric Learning with Slot Mixture Module
por: Kirilenko, Daniil, et al.
Publicado: (2023)
por: Kirilenko, Daniil, et al.
Publicado: (2023)
Improving Interpretation Faithfulness for Vision Transformers
por: Hu, Lijie, et al.
Publicado: (2023)
por: Hu, Lijie, et al.
Publicado: (2023)
Enhancing Online Continual Learning with Plug-and-Play State Space Model and Class-Conditional Mixture of Discretization
por: Liu, Sihao, et al.
Publicado: (2024)
por: Liu, Sihao, et al.
Publicado: (2024)
Caregiver Talk Shapes Toddler Vision: A Computational Study of Dyadic Play
por: Schaumlöffel, Timothy, et al.
Publicado: (2023)
por: Schaumlöffel, Timothy, et al.
Publicado: (2023)
Ortho-Hydra: Orthogonalized Experts for DiT LoRA
por: Ji, Seunghyun
Publicado: (2026)
por: Ji, Seunghyun
Publicado: (2026)
Task-conditioned Ensemble of Expert Models for Continuous Learning
por: Sharma, Renu, et al.
Publicado: (2025)
por: Sharma, Renu, et al.
Publicado: (2025)
Ejemplares similares
-
From Sparse to Soft Mixtures of Experts
por: Puigcerver, Joan, et al.
Publicado: (2023) -
Parameter-Efficient Quantized Mixture-of-Experts Meets Vision-Language Instruction Tuning for Semiconductor Electron Micrograph Analysis
por: Srinivas, Sakhinana Sagar, et al.
Publicado: (2024) -
BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma
por: Yang, Junlin, et al.
Publicado: (2026) -
Co-Supervised Learning: Improving Weak-to-Strong Generalization with Hierarchical Mixture of Experts
por: Liu, Yuejiang, et al.
Publicado: (2024) -
Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts
por: Yuan, Yike, et al.
Publicado: (2025)