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Collections including paper arxiv:2309.04354

Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts

Paper • 2309.04354 • Published Sep 8, 2023 • 14

Papers - Image - MoE - IoT

Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts

Paper • 2309.04354 • Published Sep 8, 2023 • 14
A Mixture of Expert Approach for Low-Cost Customization of Deep Neural Networks

Paper • 1811.00056 • Published Oct 31, 2018 • 2

Papers - Image - MoE

Robust Mixture-of-Expert Training for Convolutional Neural Networks

Paper • 2308.10110 • Published Aug 19, 2023 • 2
HyperFormer: Enhancing Entity and Relation Interaction for Hyper-Relational Knowledge Graph Completion

Paper • 2308.06512 • Published Aug 12, 2023 • 2
Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts

Paper • 2309.04354 • Published Sep 8, 2023 • 14
Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints

Paper • 2212.05055 • Published Dec 9, 2022 • 5

Non-asymptotic oracle inequalities for the Lasso in high-dimensional mixture of experts

Paper • 2009.10622 • Published Sep 22, 2020 • 1
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Paper • 2401.15947 • Published Jan 29, 2024 • 51
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts

Paper • 2401.04081 • Published Jan 8, 2024 • 70
MoE-Infinity: Activation-Aware Expert Offloading for Efficient MoE Serving

Paper • 2401.14361 • Published Jan 25, 2024 • 2

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 27
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

Paper • 2308.12066 • Published Aug 23, 2023 • 4
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Paper • 2303.06182 • Published Mar 10, 2023 • 1
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Paper • 2112.14397 • Published Dec 29, 2021 • 1

One Wide Feedforward is All You Need

Paper • 2309.01826 • Published Sep 4, 2023 • 32
Gated recurrent neural networks discover attention

Paper • 2309.01775 • Published Sep 4, 2023 • 8
FLM-101B: An Open LLM and How to Train It with $100K Budget

Paper • 2309.03852 • Published Sep 7, 2023 • 44
Large Language Models as Optimizers

Paper • 2309.03409 • Published Sep 7, 2023 • 76

Vision Transformers

Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts

Paper • 2309.04354 • Published Sep 8, 2023 • 14
Vision Transformers Need Registers

Paper • 2309.16588 • Published Sep 28, 2023 • 78
AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language Models

Paper • 2309.16414 • Published Sep 28, 2023 • 19
MotionLM: Multi-Agent Motion Forecasting as Language Modeling

Paper • 2309.16534 • Published Sep 28, 2023 • 15

Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts

Paper • 2309.04354 • Published Sep 8, 2023 • 14

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