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1Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models
C. Schröder, and G. Heyer. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, page 11987--12004. Miami, Florida, USA, Association for Computational Linguistics, (November 2024)
10 days ago by @chsc842f
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1BitSys: Bitwise Systolic Array Architecture for Multi-precision Quantized Hardware Accelerators
Y. Liu, S. Ullah, and A. Kumar. 2024 IEEE 32nd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), page 220-220. (2024)
2 months ago by @yuli164c
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1High-Flexibility Designs of Quantized Runtime Reconfigurable Multi-Precision Multipliers
Y. Liu, S. Rai, S. Ullah, and A. Kumar. IEEE Embedded Systems Letters, 15 (4): 194-197 (2023)
2 months ago by @yuli164c
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1NetPU-M: a Generic Reconfigurable Neural Network Accelerator Architecture for MLPs
Y. Liu, S. Rai, S. Ullah, and A. Kumar. 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), page 85-92. (2023)
2 months ago by @yuli164c
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PUMA

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1Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models

1BitSys: Bitwise Systolic Array Architecture for Multi-precision Quantized Hardware Accelerators

1High-Flexibility Designs of Quantized Runtime Reconfigurable Multi-Precision Multipliers

1NetPU-M: a Generic Reconfigurable Neural Network Accelerator Architecture for MLPs

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PUMA

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publications (hide)4 displayallpublications onlypublications per page5102050100 sort byadded attitleauthorpublication dateentry typehelp for advanced sorting... RSSBibTeXRDFmore...

1Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models

1BitSys: Bitwise Systolic Array Architecture for Multi-precision Quantized Hardware Accelerators

1High-Flexibility Designs of Quantized Runtime Reconfigurable Multi-Precision Multipliers

1NetPU-M: a Generic Reconfigurable Neural Network Accelerator Architecture for MLPs

browse

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