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Mixture-of-Experts

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Showing 76–100 of 1312 papers

TitleStatusHype
Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language ModelsCode2
MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision TasksCode2
MoEUT: Mixture-of-Experts Universal TransformersCode2
No Language Left Behind: Scaling Human-Centered Machine TranslationCode2
ReMoE: Fully Differentiable Mixture-of-Experts with ReLU RoutingCode2
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family ExpertsCode2
Mixture of A Million ExpertsCode2
Mixture of Lookup ExpertsCode2
Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer ModelsCode2
Dynamic Tuning Towards Parameter and Inference Efficiency for ViT AdaptationCode2
MiniDrive: More Efficient Vision-Language Models with Multi-Level 2D Features as Text Tokens for Autonomous DrivingCode2
ModuleFormer: Modularity Emerges from Mixture-of-ExpertsCode2
LoRA-IR: Taming Low-Rank Experts for Efficient All-in-One Image RestorationCode2
Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization AlignmentCode2
Demystifying the Compression of Mixture-of-Experts Through a Unified FrameworkCode2
MC-MoE: Mixture Compressor for Mixture-of-Experts LLMs Gains MoreCode2
Delta Decompression for MoE-based LLMs CompressionCode2
DeMo: Decoupled Feature-Based Mixture of Experts for Multi-Modal Object Re-IdentificationCode2
Mixture of Tokens: Continuous MoE through Cross-Example AggregationCode2
LLaMA-MoE v2: Exploring Sparsity of LLaMA from Perspective of Mixture-of-Experts with Post-TrainingCode2
MDFEND: Multi-domain Fake News DetectionCode2
Decomposing the Neurons: Activation Sparsity via Mixture of Experts for Continual Test Time AdaptationCode2
Learning Robust Stereo Matching in the Wild with Selective Mixture-of-ExpertsCode2
KAN4TSF: Are KAN and KAN-based models Effective for Time Series Forecasting?Code2
A Closer Look into Mixture-of-Experts in Large Language ModelsCode2
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