matlok
's Collections
Papers - MoE - Training
updated
Robust Mixture-of-Expert Training for Convolutional Neural Networks
Paper
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2308.10110
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Published
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2
Experts Weights Averaging: A New General Training Scheme for Vision
Transformers
Paper
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2308.06093
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Published
•
2
ConstitutionalExperts: Training a Mixture of Principle-based Prompts
Paper
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2403.04894
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Published
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2
Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language
Models
Paper
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2403.03432
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Published
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1
Not All Experts are Equal: Efficient Expert Pruning and Skipping for
Mixture-of-Experts Large Language Models
Paper
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2402.14800
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Published
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3
Multilinear Mixture of Experts: Scalable Expert Specialization through
Factorization
Paper
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2402.12550
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Published
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2
Buffer Overflow in Mixture of Experts
Paper
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2402.05526
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Published
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8
MegaBlocks: Efficient Sparse Training with Mixture-of-Experts
Paper
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2211.15841
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Published
•
7
Outrageously Large Neural Networks: The Sparsely-Gated
Mixture-of-Experts Layer
Paper
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1701.06538
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Published
•
5
LocMoE: A Low-overhead MoE for Large Language Model Training
Paper
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2401.13920
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Published
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2
DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to
Power Next-Generation AI Scale
Paper
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2201.05596
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Published
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2
Pipeline MoE: A Flexible MoE Implementation with Pipeline Parallelism
Paper
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2304.11414
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Published
•
2
DeepSeekMoE: Towards Ultimate Expert Specialization in
Mixture-of-Experts Language Models
Paper
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2401.06066
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Published
•
43
HyperRouter: Towards Efficient Training and Inference of Sparse Mixture
of Experts
Paper
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2312.07035
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Published
•
2
TinyLLaVA: A Framework of Small-scale Large Multimodal Models
Paper
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2402.14289
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Published
•
19
AMEND: A Mixture of Experts Framework for Long-tailed Trajectory
Prediction
Paper
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2402.08698
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Published
•
2
Fast Inference of Mixture-of-Experts Language Models with Offloading
Paper
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2312.17238
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Published
•
7
Sparse Backpropagation for MoE Training
Paper
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2310.00811
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Published
•
2
FedJETs: Efficient Just-In-Time Personalization with Federated Mixture
of Experts
Paper
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2306.08586
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Published
•
1
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with
Architecture-Routed Mixture-of-Experts
Paper
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2306.04845
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Published
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4
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
Paper
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2403.07816
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Published
•
39
Unified Scaling Laws for Routed Language Models
Paper
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2202.01169
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Published
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2
Paper
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2407.10671
•
Published
•
156