Models
Datasets
Spaces
Posts
Docs
Pricing
Log In
Sign Up

Collections

Discover the best community collections!

Collections including paper arxiv:2206.02770

MoEs papers reading list

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Paper • 1701.06538 • Published Jan 23, 2017 • 4
Sparse Networks from Scratch: Faster Training without Losing Performance

Paper • 1907.04840 • Published Jul 10, 2019 • 3
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

Paper • 1910.02054 • Published Oct 4, 2019 • 3
A Mixture of h-1 Heads is Better than h Heads

Paper • 2005.06537 • Published May 13, 2020 • 2

Papers - Multimodal

TinyLLaVA: A Framework of Small-scale Large Multimodal Models

Paper • 2402.14289 • Published Feb 22 • 16
ImageBind: One Embedding Space To Bind Them All

Paper • 2305.05665 • Published May 9, 2023 • 3
DocLLM: A layout-aware generative language model for multimodal document understanding

Paper • 2401.00908 • Published Dec 31, 2023 • 174
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts

Paper • 2206.02770 • Published Jun 6, 2022 • 3

Papers - MoE - Image

Scaling Vision with Sparse Mixture of Experts

Paper • 2106.05974 • Published Jun 10, 2021 • 3
Routers in Vision Mixture of Experts: An Empirical Study

Paper • 2401.15969 • Published Jan 29 • 2
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts

Paper • 2206.02770 • Published Jun 6, 2022 • 3
Experts Weights Averaging: A New General Training Scheme for Vision Transformers

Paper • 2308.06093 • Published Aug 11, 2023 • 2

mixture-of-experts

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Paper • 1701.06538 • Published Jan 23, 2017 • 4
Sparse Networks from Scratch: Faster Training without Losing Performance

Paper • 1907.04840 • Published Jul 10, 2019 • 3
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

Paper • 1910.02054 • Published Oct 4, 2019 • 3
A Mixture of h-1 Heads is Better than h Heads

Paper • 2005.06537 • Published May 13, 2020 • 2

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

Woodpecker: Hallucination Correction for Multimodal Large Language Models

Paper • 2310.16045 • Published Oct 24, 2023 • 13
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models

Paper • 2310.14566 • Published Oct 23, 2023 • 23
SILC: Improving Vision Language Pretraining with Self-Distillation

Paper • 2310.13355 • Published Oct 20, 2023 • 5
Conditional Diffusion Distillation

Paper • 2310.01407 • Published Oct 2, 2023 • 19

Company

© Hugging Face

TOS Privacy About Jobs

Website

Models Datasets Spaces Pricing Docs