High-quality image editing requires precise modification of target regions while preserving the content of unrelated regions. Existing editing models produce flattened outputs that limit precise local manipulation and layer reuse, while decomposition methods typically optimize layer recovery separately from instruction...
Wen Xue, Yong Liu, Xue-Heng Li et al.· 0 citations
SURE (Score-structure Utility Router for Embeddings), which improves UME-R1-7B by 1.5 points and yields consistent gains on two additional embedding models on MMEB-V2, without retraining, label-based policy selection, or extra VLM forward passes is proposed.
Wen-Xiao Fan, Jing-Ling Fu, Lu Liu et al.· 0 citations
This work presents TryOnReward, a fine-grained reward model tailored for VTON that significantly outperforms generic judges in human preference alignment, and when serving as the RFT reward function, it consistently yields human-preferred try-on results across multiple baselines.
Xue-Heng Li, Yong Liu, Xiao-Long Fu et al.· 0 citations
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