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Accelerating Transformers with Spectrum-Preserving Token Merging

, , , , , , , , , and . In Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), (2024)
DOI: https://doi.org/10.48550/arXiv.2405.16148

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Accelerating Transformers with Spectrum-Preserving Token Merging, , , , , , , , , and . In Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), (2024)Automatically Generate Hymns Using Variational Attention Models., , , and . ISNN (2), volume 11555 of Lecture Notes in Computer Science, page 317-327. Springer, (2019)Fast learning rates with heavy-tailed losses., , , and . CoRR, (2016)An active learning framework for set inversion., , , and . Knowl.-Based Syst., (2019)Learning from Non-iid Data: Fast Rates for the One-vs-All Multiclass Plug-in Classifiers., , , , and . TAMC, volume 9076 of Lecture Notes in Computer Science, page 375-387. Springer, (2015)OASIS: An Active Framework for Set Inversion., , , and . SoMeT, volume 303 of Frontiers in Artificial Intelligence and Applications, page 883-895. IOS Press, (2018)3D-Brain Segmentation Using Deep Neural Network and Gaussian Mixture Model., , , and . WACV, page 815-824. IEEE Computer Society, (2017)