3 papers
cs.CV2026
GuidedBridge: Training-freely Improving Bridge Models with Prior Guidance
Zehua Chen, Yucheng Yang, Binjie Yuan +3
Guidance methods, such as classifier-free guidance (CFG) and auto-guidance (AG), have advanced noise-to-data generation in diffusion models. Recently, bridge models have introduced…
cs.SD2025
AudioMoG: Guiding Audio Generation with Mixture-of-Guidance
Junyou Wang, Zehua Chen, Binjie Yuan +4
The design of diffusion-based audio generation systems has been investigated from diverse perspectives, such as data space, network architecture, and conditioning techniques, while…
cs.LG2018
ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies
Bao Wang, Binjie Yuan, Zuoqiang Shi +1
Empirical adversarial risk minimization (EARM) is a widely used mathematical framework to robustly train deep neural nets (DNNs) that are resistant to adversarial attacks. However,…