Copertina

Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Jiang, Songtao, Zheng, Tuo, Zhang, Yan, Jin, Yeying, Yuan, Li, Liu, Zuozhu
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

HSCR: Hierarchical Self-Contrastive Rewarding for Aligning Medical Vision Language Models
di: Jiang, Songtao, et al.
Pubblicazione: (2025)

Fair-MoE: Fairness-Oriented Mixture of Experts in Vision-Language Models
di: Wang, Peiran, et al.
Pubblicazione: (2025)

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
di: Lin, Bin, et al.
Pubblicazione: (2024)

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

MedMoE: Modality-Specialized Mixture of Experts for Medical Vision-Language Understanding
di: Chopra, Shivang, et al.
Pubblicazione: (2025)

CP-MoE: Consistency-Preserving Mixture-of-Experts for Continual Learning
di: Liu, Yang, et al.
Pubblicazione: (2026)

3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow
di: Ma, Yueen, et al.
Pubblicazione: (2025)

MoE-GS: Mixture of Experts for Dynamic Gaussian Splatting
di: Jin, In-Hwan, et al.
Pubblicazione: (2025)

MoE-GRPO: Optimizing Mixture-of-Experts via Reinforcement Learning in Vision-Language Models
di: Ko, Dohwan, et al.
Pubblicazione: (2026)

MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping
di: Huang, Yushi, et al.
Pubblicazione: (2025)

MedCoT: Medical Chain of Thought via Hierarchical Expert
di: Liu, Jiaxiang, et al.
Pubblicazione: (2024)

EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE
di: Chen, Junyi, et al.
Pubblicazione: (2023)

SAM-Med3D-MoE: Towards a Non-Forgetting Segment Anything Model via Mixture of Experts for 3D Medical Image Segmentation
di: Wang, Guoan, et al.
Pubblicazione: (2024)

Uni-MoE-2.0-Omni: Scaling Language-Centric Omnimodal Large Model with Advanced MoE, Training and Data
di: Li, Yunxin, et al.
Pubblicazione: (2025)

RS-MoE: A Vision-Language Model with Mixture of Experts for Remote Sensing Image Captioning and Visual Question Answering
di: Lin, Hui, et al.
Pubblicazione: (2024)

GM-MoE: Low-Light Enhancement with Gated-Mechanism Mixture-of-Experts
di: Liao, Minwen, et al.
Pubblicazione: (2025)

OmniV-Med: Scaling Medical Vision-Language Model for Universal Visual Understanding
di: Jiang, Songtao, et al.
Pubblicazione: (2025)

Med-GLIP: Advancing Medical Language-Image Pre-training with Large-scale Grounded Dataset
di: Deng, Ziye, et al.
Pubblicazione: (2025)

Fast or Slow? Integrating Fast Intuition and Deliberate Thinking for Enhancing Visual Question Answering
di: Jiang, Songtao, et al.
Pubblicazione: (2025)

ChartMoE: Mixture of Diversely Aligned Expert Connector for Chart Understanding
di: Xu, Zhengzhuo, et al.
Pubblicazione: (2024)

MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language Models
di: Yan, Qiao, et al.
Pubblicazione: (2025)

MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision Tasks
di: Zhu, Xingkui, et al.
Pubblicazione: (2024)

MoE-FFD: Mixture of Experts for Generalized and Parameter-Efficient Face Forgery Detection
di: Kong, Chenqi, et al.
Pubblicazione: (2024)

TemMed-Bench: Evaluating Temporal Medical Image Reasoning in Vision-Language Models
di: Zhang, Junyi, et al.
Pubblicazione: (2025)

Lifelong Knowledge Editing for Vision Language Models with Low-Rank Mixture-of-Experts
di: Chen, Qizhou, et al.
Pubblicazione: (2024)

Adapted-MoE: Mixture of Experts with Test-Time Adaption for Anomaly Detection
di: Lei, Tianwu, et al.
Pubblicazione: (2024)

Semi-MoE: Mixture-of-Experts meets Semi-Supervised Histopathology Segmentation
di: Vu, Nguyen Lan Vi, et al.
Pubblicazione: (2025)

MedCLIPSeg: Probabilistic Vision-Language Adaptation for Data-Efficient and Generalizable Medical Image Segmentation
di: Koleilat, Taha, et al.
Pubblicazione: (2026)

MoME: Mixture of Visual Language Medical Experts for Medical Imaging Segmentation
di: Rezvani, Arghavan, et al.
Pubblicazione: (2025)

MoPD: Mixture-of-Prompts Distillation for Vision-Language Models
di: Chen, Yang, et al.
Pubblicazione: (2024)

MoEController: Instruction-based Arbitrary Image Manipulation with Mixture-of-Expert Controllers
di: Li, Sijia, et al.
Pubblicazione: (2023)

Patch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation
di: Adame, Diego, et al.
Pubblicazione: (2026)

TAG-MoE: Task-Aware Gating for Unified Generative Mixture-of-Experts
di: Xu, Yu, et al.
Pubblicazione: (2026)

SocialNav-MoE: A Mixture-of-Experts Vision Language Model for Socially Compliant Navigation with Reinforcement Fine-Tuning
di: Kawabata, Tomohito, et al.
Pubblicazione: (2025)

Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding
di: Jiang, Songtao, et al.
Pubblicazione: (2025)

MoE3D: A Mixture-of-Experts Module for 3D Reconstruction
di: Wang, Zichen, et al.
Pubblicazione: (2026)

R^2MoE: Redundancy-Removal Mixture of Experts for Lifelong Concept Learning
di: Guo, Xiaohan, et al.
Pubblicazione: (2025)

CBDES MoE: Hierarchically Decoupled Mixture-of-Experts for Functional Modules in Autonomous Driving
di: Xiang, Qi, et al.
Pubblicazione: (2025)

Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE
di: Chen, Zeren, et al.
Pubblicazione: (2023)

Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models
di: Luo, Jun, et al.
Pubblicazione: (2024)