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cs.CV2026
HimmBO: High-Dimensional Interactive Model-Merging Bayesian Optimization for Image Generation
Jinyuan Mao, Zhihao Shen, Chenxi Liu
Fine-tuning has become a common way to customize text-to-image models, leading to community collections of over 100K lightweight adapters. Adapters sharing a base model can be merg…
cs.CV2026
SemLayer: Semantic-aware Generative Segmentation and Layer Construction for Abstract Icons
Haiyang Xu, Ronghuan Wu, Li-Yi Wei +5
Graphic icons are a cornerstone of modern design workflows, yet they are often distributed as flattened single-path or compound-path graphics, where the original semantic layering…
cs.CV2026
GimmBO: Interactive Generative Image Model Merging via Bayesian Optimization
Chenxi Liu, Selena Ling, Alec Jacobson
Fine-tuning-based adaptation is widely used to customize diffusion-based image generation, leading to large collections of community-created adapters that capture diverse subjects…