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JarvisHub: An Open Harness for Canvas-Native Multimodal Creative Agents
Yunlong Lin, Zixu Lin, Zhaohu Xing +23
Creative AI is moving from single-step asset generation toward long-horizon multimodal production. Although recent generative models can synthesize high-quality images, videos, aud…
GEAR: Guided End-to-End AutoRegression for Image Synthesis
Bin Lin, Zheyuan Liu, Chenguo Lin +8
Visual generative models are typically trained in two stages. A tokenizer is first trained for reconstruction and then frozen, after which a generator is trained on its discrete in…
SegDINO: Introducing Multi-Scale Structure into DINO for Efficient Medical Image Segmentation
Sicheng Yang, Hongqiu Wang, Zhaohu Xing +5
Self-supervised DINO models provide strong transferable visual representations, yet applying them directly to image segmentation remains challenging. Existing approaches commonly r…
GenEvolve: Self-Evolving Image Generation Agents via Tool-Orchestrated Visual Experience Distillation
Sixiang Chen, Zhaohu Xing, Tian Ye +7
Open-ended image generation is no longer a simple prompt-to-image problem. High-quality generation often requires an agent to combine a model's internal generative ability with ext…
Latent Action Control for Reasoning-Guided Unified Image Generation
Fuxiang Zhai, Sixiang Chen, Yingjin Li +4
Unified multimodal models can encode visual understanding and image generation within a shared backbone, yet understanding does not automatically translate into control: models may…
LucidNFT: LR-Anchored Multi-Reward Preference Optimization for Flow-Based Real-World Super-Resolution
Song Fei, Tian Ye, Sixiang Chen +3
Generative real-world image super-resolution (Real-ISR) can synthesize visually convincing details from severely degraded low-resolution (LR) inputs, yet its stochastic sampling ma…