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Mixture-of-Experts

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Showing 176–200 of 1312 papers

TitleStatusHype
FedMerge: Federated Personalization via Model Merging—0
MoEDiff-SR: Mixture of Experts-Guided Diffusion Model for Region-Adaptive MRI Super-ResolutionCode1
Finding Fantastic Experts in MoEs: A Unified Study for Expert Dropping Strategies and Observations—0
HybriMoE: Hybrid CPU-GPU Scheduling and Cache Management for Efficient MoE InferenceCode2
RingMoE: Mixture-of-Modality-Experts Multi-Modal Foundation Models for Universal Remote Sensing Image Interpretation—0
HeterMoE: Efficient Training of Mixture-of-Experts Models on Heterogeneous GPUs—0
MiLo: Efficient Quantized MoE Inference with Mixture of Low-Rank CompensatorsCode1
MegaScale-Infer: Serving Mixture-of-Experts at Scale with Disaggregated Expert Parallelism—0
Advancing MoE Efficiency: A Collaboration-Constrained Routing (C2R) Strategy for Better Expert Parallelism Design—0
A Unified Virtual Mixture-of-Experts Framework:Enhanced Inference and Hallucination Mitigation in Single-Model System—0
Detecting Financial Fraud with Hybrid Deep Learning: A Mix-of-Experts Approach to Sequential and Anomalous Patterns—0
DynMoLE: Boosting Mixture of LoRA Experts Fine-Tuning with a Hybrid Routing MechanismCode0
Unimodal-driven Distillation in Multimodal Emotion Recognition with Dynamic Fusion—0
Mixture of Routers—0
Sparse Mixture of Experts as Unified Competitive Learning—0
S2MoE: Robust Sparse Mixture of Experts via Stochastic Learning—0
Beyond Standard MoE: Mixture of Latent Experts for Resource-Efficient Language Models—0
Exploiting Mixture-of-Experts Redundancy Unlocks Multimodal Generative Abilities—0
RocketPPA: Code-Level Power, Performance, and Area Prediction via LLM and Mixture of Experts—0
LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models—0
iMedImage Technical Report—0
A multi-scale lithium-ion battery capacity prediction using mixture of experts and patch-based MLPCode0
Reasoning Beyond Limits: Advances and Open Problems for LLMs—0
Enhancing Multi-modal Models with Heterogeneous MoE Adapters for Fine-tuning—0
Optimal Scaling Laws for Efficiency Gains in a Theoretical Transformer-Augmented Sectional MoE Framework—0
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