Instruction-driven image editing has reached native 4K, yet how such editors are trained remains undisclosed, and pretraining one from scratch is beyond most teams. The task itself compounds the difficulty: a single end-to-end editor cannot make precise parametric adjustments, match specialized experts, or interpret th...
Shan-Yan Guan, Shi-Yu Li, Xin Li et al.· 0 citations
This work proposes REST (Reward-Enhanced Scored-Trajectory Distillation), a single-stage RL-distillation co-training framework that attaches a decoupled student to an arbitrary RL teacher that enables few-step CFG-free inference that matches or surpasses its 40-step RL teacher, with an overall additional training cost...
Yuhan Li, Fan-Gao Zeng, Sicong Kang et al.· 0 citations
A novel post-training acceleration framework that exploits this redundancy by integrating dynamic structural sparsification directly into the distillation process, and introduces a Progressive Training Strategy coupled with an Output Rollout Mechanism that ensures the coherent learning of structural decisions across ti...
Yu Cheng, Siyue Yao, Zhongang Qi et al.· 0 citations
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