Papers with multimodal machine learning applications

1 papers
Scaling Vision-Language Models with Sparse Mixture of Experts (2023.findings-emnlp)

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Challenge: a study explores the effectiveness of mixture-of-experts (MoE) techniques in scaling vision-language models . alayrac and colleagues demonstrate the effectiveness and performance of MoE in scaling VLMs .
Approach: They propose to use sparsely-gated mixture-of-experts techniques to scale vision-language models . they show that MoE can achieve state-of the-art performance over dense models a range of benchmarks .
Outcome: The proposed approach achieves state-of-the-art performance over dense models of equivalent computational cost.

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