2 papers
cs.LG2026
JIVE: Jacobian-Informed Volume Expansion for Diverse Generative Sampling
Guangxun Zhang, Brian Cai, Boxuan Zhang +2
Generative models often suffer from mode collapse and limited sample diversity. While prior works attempt to mitigate this by jointly generating a batch of samples and repelling th…
cs.CV2026
Model the Edit, Not the Image: Visual Autoregressive Editing from a Source-Centric Perspective
Hongyi Fang, Chuwen Xie, Benjia Zhou +6
Next-scale visual autoregressive models (VARs) have emerged as a powerful generative paradigm, producing high-quality images through efficient coarse-to-fine prediction. However, t…