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Collections including paper arxiv:2404.15045

Mixture of Experts

BlackMamba: Mixture of Experts for State-Space Models

Paper • 2402.01771 • Published Feb 1, 2024 • 24
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models

Paper • 2402.01739 • Published Jan 29, 2024 • 27
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Paper • 2401.15947 • Published Jan 29, 2024 • 51
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11, 2024 • 49

YOLO-World: Real-Time Open-Vocabulary Object Detection

Paper • 2401.17270 • Published Jan 30, 2024 • 36
Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities

Paper • 2401.14405 • Published Jan 25, 2024 • 13
Improving fine-grained understanding in image-text pre-training

Paper • 2401.09865 • Published Jan 18, 2024 • 17
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data

Paper • 2404.15653 • Published Apr 24, 2024 • 27

MoEs papers reading list

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

Paper • 1701.06538 • Published Jan 23, 2017 • 5
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 • 4
A Mixture of h-1 Heads is Better than h Heads

Paper • 2005.06537 • Published May 13, 2020 • 2

ChatAnything: Facetime Chat with LLM-Enhanced Personas

Paper • 2311.06772 • Published Nov 12, 2023 • 35
Fine-tuning Language Models for Factuality

Paper • 2311.08401 • Published Nov 14, 2023 • 29
A Survey on Language Models for Code

Paper • 2311.07989 • Published Nov 14, 2023 • 22
Instruction-Following Evaluation for Large Language Models

Paper • 2311.07911 • Published Nov 14, 2023 • 20

Ultra-Long Sequence Distributed Transformer

Paper • 2311.02382 • Published Nov 4, 2023 • 6
Ziya2: Data-centric Learning is All LLMs Need

Paper • 2311.03301 • Published Nov 6, 2023 • 19
Relax: Composable Abstractions for End-to-End Dynamic Machine Learning

Paper • 2311.02103 • Published Nov 1, 2023 • 20
Extending Context Window of Large Language Models via Semantic Compression

Paper • 2312.09571 • Published Dec 15, 2023 • 15

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

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