Towards Energy-Preserving Natural Language Understanding With Spiking Neural Networks-Reference-Cited by-同舟云学术

Towards Energy-Preserving Natural Language Understanding With Spiking Neural Networks

Author:

Xiao Rong¹^ORCID,Wan Yu²^ORCID,Yang Baosong¹^ORCID,Zhang Haibo¹^ORCID,Tang Huajin³^ORCID,Wong Derek F.²^ORCID,Chen Boxing¹^ORCID

Affiliation:

1. Damo Academy, Alibaba Group, Hangzhou, China

2. NLP CT Lab, University of Macau, Macao, China

3. Zhejiang University, Hangzhou, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Science and Technology Development Fund, Macau SAR

Multi-year Research Grant from the University of Macau

Alibaba Group

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics

Link

Reference39 articles.

3. Synthesizer: Rethinking self-attention for transformer models;tay;Proc Int Conf Mach Learn,0

4. DIET-SNN: Direct input encoding with leakage and threshold optimization in deep spiking neural networks;rathi,2020

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. An embedded end-to-end voice assistant;Engineering Applications of Artificial Intelligence;2024-10