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cs.CV2026
Learning to Generate via Understanding: Understanding-Driven Intrinsic Rewarding for Unified Multimodal Models
Jiadong Pan, Liang Li, Yuxin Peng +6
Recently, unified multimodal models (UMMs) have made remarkable progress in integrating visual understanding and generation, demonstrating strong potential for complex text-to-imag…
cs.CV2025
Self-Reflective Reinforcement Learning for Diffusion-based Image Reasoning Generation
Jiadong Pan, Zhiyuan Ma, Kaiyan Zhang +2
Diffusion models have recently demonstrated exceptional performance in image generation task. However, existing image generation methods still significantly suffer from the dilemma…
cs.CV2024
SafeCFG: Controlling Harmful Features with Dynamic Safe Guidance for Safe Generation
Jiadong Pan, Liang Li, Hongcheng Gao +3
Diffusion models (DMs) have demonstrated exceptional performance in text-to-image tasks, leading to their widespread use. With the introduction of classifier-free guidance (CFG), t…