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SPViT: Enabling Faster Vision Transformers via Latency-Aware Soft Token Pruning.

Z. Kong, P. Dong, X. Ma, X. Meng, W. Niu, M. Sun, X. Shen, G. Yuan, B. Ren, H. Tang, M. Qin, and Y. Wang. ECCV (11), volume 13671 of Lecture Notes in Computer Science, page 620-640. Springer, (2022)

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Michael Döngi

Purinerge und GAbAerge Calciumsignale in Astrozyten des Bulbus olfactorius der MausM. Döngi. TU Kaiserslautern, (2009)

Dong Chen

Acceleration of the spatial selective excitation of MRI via sparse approximationD. Chen. TU München, (2009)

Dieter Dönges

Manfred Dönges

Klaus Georg Dönges

Other publications of authors with the same name

Puncturing the memory wall: Joint optimization of network compression with approximate memory for ASR application.Q. Li, P. Dong, Z. Yu, C. Liu, F. Qiao, Y. Wang, and H. Yang. ASP-DAC, page 505-511. ACM, (2021)EdgeQAT: Entropy and Distribution Guided Quantization-Aware Training for the Acceleration of Lightweight LLMs on the Edge.X. Shen, Z. Kong, C. Yang, Z. Han, L. Lu, P. Dong, C. Lyu, C. hsiang Li, X. Guo, Z. Shu and 4 other author(s). CoRR, (2024)SPViT: Enabling Faster Vision Transformers via Soft Token Pruning.Z. Kong, P. Dong, X. Ma, X. Meng, W. Niu, M. Sun, B. Ren, M. Qin, H. Tang, and Y. Wang. CoRR, (2021)GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices Based on Fine-Grained Structured Weight Sparsity.W. Niu, Z. Li, X. Ma, P. Dong, G. Zhou, X. Qian, X. Lin, Y. Wang, and B. Ren. IEEE Trans. Pattern Anal. Mach. Intell., 44 (10): 6224-6239 (2022)TAAS: a timing-aware analytical strategy for AQFP-capable placement automation.P. Dong, Y. Xie, H. Li, M. Sun, O. Chen, N. Yoshikawa, and Y. Wang. DAC, page 1321-1326. ACM, (2022)CSB-RNN: a faster-than-realtime RNN acceleration framework with compressed structured blocks.R. Shi, P. Dong, T. Geng, Y. Ding, X. Ma, H. So, M. Herbordt, A. Li, and Y. Wang. ICS, page 24:1-24:12. ACM, (2020)Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge.X. Shen, P. Dong, L. Lu, Z. Kong, Z. Li, M. Lin, C. Wu, and Y. Wang. AAAI, page 18944-18951. AAAI Press, (2024)Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework.G. Yuan, P. Dong, M. Sun, W. Niu, Z. Li, Y. Cai, Y. Li, J. Liu, W. Jiang, X. Lin and 3 other author(s). ACM Trans. Embed. Comput. Syst., 21 (5): 65:1-65:22 (September 2022)HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers.P. Dong, M. Sun, A. Lu, Y. Xie, K. Liu, Z. Kong, X. Meng, Z. Li, X. Lin, Z. Fang and 1 other author(s). CoRR, (2022)RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition.P. Dong, S. Wang, W. Niu, C. Zhang, S. Lin, Z. Li, Y. Gong, B. Ren, X. Lin, Y. Wang and 1 other author(s). CoRR, (2020)

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Disambiguation of "Dong, Peiyan"

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SPViT: Enabling Faster Vision Transformers via Latency-Aware Soft Token Pruning.

Please choose a person to relate this publication to

Michael Döngi

Dong Chen

Dieter Dönges

Manfred Dönges

Klaus Georg Dönges

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Dong, Peiyan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML SPViT: Enabling Faster Vision Transformers via Latency-Aware Soft Token Pruning.

Please choose a person to relate this publication to

Michael Döngi

Dong Chen

Dieter Dönges

Manfred Dönges

Klaus Georg Dönges

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
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SPViT: Enabling Faster Vision Transformers via Latency-Aware Soft Token Pruning.