2 papers
cs.AI2025
Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings
Yifei Peng, Zijie Zha, Yu Jin +5
Making neural visual generative models controllable by logical reasoning systems is promising for improving faithfulness, transparency, and generalizability. We propose the Abducti…
cs.LG2025
Pre-Training Meta-Rule Selection Policy for Visual Generative Abductive Learning
Yu Jin, Jingming Liu, Zhexu Luo +5
Visual generative abductive learning studies jointly training symbol-grounded neural visual generator and inducing logic rules from data, such that after learning, the visual gener…