2 citations · 2 across the 10 of their papers we have counts for
4 papers · 1 filter
Disentangling 3D Modeling from Spatial Reasoning
Haoze Sun, Jiequan Cui, Qingshan Xu +1
In this work, we explore an alternative paradigm for spatial reasoning by explicitly disentangling 3D perception from reasoning, rather than jointly acquiring implicit 3D perceptio…
Generative Distribution Distillation
Jiequan Cui, Beier Zhu, Qingshan Xu +6
In this paper, we formulate the knowledge distillation (KD) as a conditional generative problem and propose the \textit{Generative Distribution Distillation (GenDD)} framework. A n…
Your Classifier Can Do More: Towards Balancing the Gaps in Classification, Robustness, and Generation
Kaichao Jiang, He Wang, Xiaoshuai Hao +5
Joint Energy-based Models (JEMs) are well known for their ability to unify classification and generation within a single framework. Despite their promising generative and discrimin…
Generalized Kullback-Leibler Divergence Loss
Jiequan Cui, Beier Zhu, Qingshan Xu +5
In this paper, we delve deeper into the Kullback-Leibler (KL) Divergence loss and mathematically prove that it is equivalent to the Decoupled Kullback-Leibler (DKL) Divergence loss…