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Mixture-of-Experts

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Showing 776–800 of 1312 papers

TitleStatusHype
FineQuant: Unlocking Efficiency with Fine-Grained Weight-Only Quantization for LLMs—0
FinTeamExperts: Role Specialized MOEs For Financial Analysis—0
Fixing MoE Over-Fitting on Low-Resource Languages in Multilingual Machine Translation—0
Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models—0
FlexMoE: Scaling Large-scale Sparse Pre-trained Model Training via Dynamic Device Placement—0
FloE: On-the-Fly MoE Inference on Memory-constrained GPU—0
fMoE: Fine-Grained Expert Offloading for Large Mixture-of-Experts Serving—0
FMT:A Multimodal Pneumonia Detection Model Based on Stacking MOE Framework—0
ForceVLA: Enhancing VLA Models with a Force-aware MoE for Contact-rich Manipulation—0
Free Agent in Agent-Based Mixture-of-Experts Generative AI Framework—0
FreqMoE: Dynamic Frequency Enhancement for Neural PDE Solvers—0
Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning—0
From Google Gemini to OpenAI Q* (Q-Star): A Survey of Reshaping the Generative Artificial Intelligence (AI) Research Landscape—0
FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models—0
Full-Precision Free Binary Graph Neural Networks—0
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs—0
Functional mixture-of-experts for classification—0
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion—0
FuxiMT: Sparsifying Large Language Models for Chinese-Centric Multilingual Machine Translation—0
Galaxy Walker: Geometry-aware VLMs For Galaxy-scale Understanding—0
Gated Ensemble of Spatio-temporal Mixture of Experts for Multi-task Learning in Ride-hailing System—0
Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers—0
GEMNET: Effective Gated Gazetteer Representations for Recognizing Complex Entities in Low-context Input—0
Generalizable Person Re-identification with Relevance-aware Mixture of Experts—0
Generalization Error Analysis for Sparse Mixture-of-Experts: A Preliminary Study—0
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