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  1. 1
    Pruning One More Token is Enough: Leveraging Latency-Workload Non-Linearities for Vision Transformers on the Edge

    Pruning One More Token is Enough: Leveraging Latency-Workload Non-Linearities for Vision Transformers on the Edge von Eliopoulos, Nick John, Jajal, Purvish, Davis, James C, Liu, Gaowen, Thiravathukal, George K, Lu, Yung-Hsiang

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  2. 2
    Token Turing Machines are Efficient Vision Models

    Token Turing Machines are Efficient Vision Models von Jajal, Purvish, Eliopoulos, Nick John, Chou, Benjamin Shiue-Hal, Thiravathukal, George K, Davis, James C, Lu, Yung-Hsiang

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  3. 3
    Pruning One More Token is Enough: Leveraging Latency-Workload Non-Linearities for Vision Transformers on the Edge

    Pruning One More Token is Enough: Leveraging Latency-Workload Non-Linearities for Vision Transformers on the Edge von Eliopoulos, Nick John, Jajal, Purvish, Davis, James C, Liu, Gaowen, Thiravathukal, George K, Lu, Yung-Hsiang

    Veröffentlicht in arXiv.org

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  4. 4
    Token Turing Machines are Efficient Vision Models

    Token Turing Machines are Efficient Vision Models von Jajal, Purvish, Eliopoulos, Nick John, Chou, Benjamin Shiue-Hal, Thiravathukal, George K, Davis, James C, Lu, Yung-Hsiang

    Veröffentlicht in arXiv.org

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