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Collections including paper arxiv:2310.00811

Papers - MoE - Router

Turn Waste into Worth: Rectifying Top-k Router of MoE

Paper • 2402.12399 • Published Feb 17, 2024 • 2
CompeteSMoE -- Effective Training of Sparse Mixture of Experts via Competition

Paper • 2402.02526 • Published Feb 4, 2024 • 3
Buffer Overflow in Mixture of Experts

Paper • 2402.05526 • Published Feb 8, 2024 • 8
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models

Paper • 2402.01739 • Published Jan 29, 2024 • 26

Papers - MoE - Training

Robust Mixture-of-Expert Training for Convolutional Neural Networks

Paper • 2308.10110 • Published Aug 19, 2023 • 2
Experts Weights Averaging: A New General Training Scheme for Vision Transformers

Paper • 2308.06093 • Published Aug 11, 2023 • 2
ConstitutionalExperts: Training a Mixture of Principle-based Prompts

Paper • 2403.04894 • Published Mar 7, 2024 • 2
Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models

Paper • 2403.03432 • Published Mar 6, 2024 • 1

Papers - MoE - Research

Adaptive sequential Monte Carlo by means of mixture of experts

Paper • 1108.2836 • Published Aug 14, 2011 • 2
Convergence Rates for Mixture-of-Experts

Paper • 1110.2058 • Published Oct 10, 2011 • 2
Multi-view Contrastive Learning for Entity Typing over Knowledge Graphs

Paper • 2310.12008 • Published Oct 18, 2023 • 2
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts

Paper • 2308.11793 • Published Aug 22, 2023 • 2

MOE papers to read

Copied from MoE using https://huggingface.co/spaces/librarian-bots/collection_cloner.

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

Paper • 2310.16795 • Published Oct 25, 2023 • 26
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

Backpropagation

Sparse Backpropagation for MoE Training

Paper • 2310.00811 • Published Oct 1, 2023 • 2
The Forward-Forward Algorithm: Some Preliminary Investigations

Paper • 2212.13345 • Published Dec 27, 2022 • 2
Fine-Tuning Language Models with Just Forward Passes

Paper • 2305.17333 • Published May 27, 2023 • 2
Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Paper • 2309.13192 • Published Sep 22, 2023 • 1

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

Paper • 2310.16795 • Published Oct 25, 2023 • 26
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

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