Zengjie Song — accepted AI-conference papers

2026

Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization

Chengli Tan, Yubo Zhou, Haishan Ye, Guang Dai, Junmin Liu, Zengjie Song +4

ICLR 2026poster

Deep neural networks have been increasingly used in safety-critical applications such as medical diagnosis and autonomous driving. However, many studies suggest that they are prone to being poorly calibrated and have a propensity for overconfidence, which may have disastrous consequences. In this pa…

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2023

SSF: Accelerating Training of Spiking Neural Networks with Stabilized Spiking Flow

Jingtao Wang, Zengjie Song, Yuxi Wang, Jun Xiao, Yuran Yang, Shuqi Mei +1

ICCV 2023poster

Surrogate gradient (SG) is one of the most effective approaches for training spiking neural networks (SNNs). While assisting SNNs to achieve classification performance comparable to artificial neural networks, SG suffers from the problem of time-consuming training, preventing it from efficient learn…

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