2 citations · 5 across the 10 of their papers we have counts for
Showing 2025Show all
3 papers · 1 filter
cs.CV2025
Dropout Prompt Learning: Towards Robust and Adaptive Vision-Language Models
Biao Chen, Lin Zuo, Mengmeng Jing +2
Dropout is a widely used regularization technique which improves the generalization ability of a model by randomly dropping neurons. In light of this, we propose Dropout Prompt Lea…
cs.LG2025
Synergy Between the Strong and the Weak: Spiking Neural Networks are Inherently Self-Distillers
Yongqi Ding, Lin Zuo, Mengmeng Jing +3
Brain-inspired spiking neural networks (SNNs) promise to be a low-power alternative to computationally intensive artificial neural networks (ANNs), although performance gaps persis…
cs.LG2025★ 1 cited
Rethinking Spiking Neural Networks from an Ensemble Learning Perspective
Yongqi Ding, Lin Zuo, Mengmeng Jing +2
Spiking neural networks (SNNs) exhibit superior energy efficiency but suffer from limited performance. In this paper, we consider SNNs as ensembles of temporal subnetworks that sha…