no code implementations • 19 May 2023 • Xiaowei Huang, Wenjie Ruan, Wei Huang, Gaojie Jin, Yi Dong, Changshun Wu, Saddek Bensalem, Ronghui Mu, Yi Qi, Xingyu Zhao, Kaiwen Cai, Yanghao Zhang, Sihao Wu, Peipei Xu, Dengyu Wu, Andre Freitas, Mustafa A. Mustafa
Large Language Models (LLMs) have exploded a new heatwave of AI for their ability to engage end-users in human-level conversations with detailed and articulate answers across many knowledge domains.
1 code implementation • CVPR 2023 • Gaojie Jin, Xinping Yi, Dengyu Wu, Ronghui Mu, Xiaowei Huang
The randomized weights enable our design of a novel adversarial training method via Taylor expansion of a small Gaussian noise, and we show that the new adversarial training method can flatten loss landscape and find flat minima.
1 code implementation • 23 Jan 2023 • Dengyu Wu, Gaojie Jin, Han Yu, Xinping Yi, Xiaowei Huang
The Top-K cutoff technique optimises the inference of SNN, and the regularisation are proposed to affect the training and construct SNN with optimised performance for cutoff.
1 code implementation • 1 Mar 2021 • Dengyu Wu, Xinping Yi, Xiaowei Huang
In this paper, we argue that this trend of "energy for accuracy" is not necessary -- a little energy can go a long way to achieve the near-zero accuracy loss.