🎨 A new unified visual AI where "seeing" and "creating" get trained to reinforce each other in one shared model. Title: SenseNova-U1.5: Towards Native Unified Visual Intelligence URL: 🧩 Overview OpenSenseNova's 8B Mixture-of-Transformers model drops external vision encoders and VAEs entirely, processing raw pixels directly while handling image understanding, reasoning, generation, and editing in one model. ⚙️ Problem it solves Most unified models route understanding and generation through separate latent spaces, causing consistency loss. This work aims to truly unify them on one shared representation. 🛠 Methodology Visual tokens are projected onto a 2D feature field and reconstructed with a spatial decoder that exchanges info across neighboring 32×32 regions. Four specialized experts (aesthetics, OCR, editing, infographics) are trained separately with RL, then merged into one model via On-Policy Distillation. 📊 Results GenEval overall hits 0.92, ImgEdit reaches 4.59 (up from 3.90 in U1), and BizGenEval jumps from 51.4% to 72.2% — outperforming its predecessor and competitors across understanding, generation, and editing alike. #UnifiedMultimodalAI# #ImageGeneration#