SenseNova-U1.5: Towards Native Unified Visual Intelligence
We launch SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free and VAE-free architecture. We strengthen its visual interface through spatially coherent patch reconstruction and scale its training with carefully curated generation and editing data, improved task formulation, structural prompt enhancement, and native resolutions of up to 4K. For post-training, we optimize specialized experts for visual aesthetics, bilingual text rendering, infographic generation, and image editing, and consolidate their cap
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- PossiblePossibly related (embedding) · 61%NeoMME: an efficient Multimodal-native and Multilingual Encoder →
- PossiblePossibly related (embedding) · 59%STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation - Apple Machine Learning Research →
- FuzzyOverlapping authors or contributors · 78%sgl-project/sglang →
“Shared author/contributor keys: luo, zhou”
- FuzzyOverlapping authors or contributors · 62%Kong/kong →
“Shared author/contributor keys: kong”
- FuzzyOverlapping authors or contributors · 62%ray-project/ray →
“Shared author/contributor keys: wang”
- FuzzyOverlapping authors or contributors · 62%Zeyi-Lin/HivisionIDPhotos →
“Shared author/contributor keys: lin”
- FuzzyOverlapping authors or contributors · 62%google-research/google-research →
“Shared author/contributor keys: sun”