Papers by Jeongyoon Moon

    1 papers
    MOSEL: Inference Serving Using Dynamic Modality Selection (2024.emnlp-main)

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    Challenge: Recent advances in machine learning have enabled deep learning to exceed human capabilities in various tasks.
    Approach: They propose a new form of dynamism, modality selection, where modality picks modalities from inference inputs while maintaining the model quality.
    Outcome: The proposed system improves system throughput by 3.6 and job completion times by 11 compared to modality-agnostic approaches.

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