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20232026
most citedParagraph-to-Image Generation with Information-Enriched Diffusion Model

1 citations · 2 across the 9 of their papers we have counts for

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cs.CV2026

Learning Native Reflection in Unified Models with Interleaved Reinforcement Learning

Yijia Fan, Ziqi Huang, Zhongang Cai +5

Unified multimodal models can both look at and render images, so in principle they can repair their own generations: diagnose what an image gets wrong, revise it, observe the resul…

cs.CV2026

SenseNova-U1.5: Towards Native Unified Visual Intelligence

Haiwen Diao, Jiahao Wang, Chenjing Ding +62

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.…

cs.CV2026

LiWi: Layering in the Wild

Yu He, Fang Li, Haoyang Tong +7

Recent advances in generative models have empowered impressive layered image generation, yet their success is largely confined to graphic design domains. The layering of in-the-wil…

cs.CV2026

Fashion130K: An E-commerce Fashion Dataset for Outfit Generation with Unified Multi-modal Condition

Yu He, Ting Zhu, Yichun Liu +6

Recent research work on fashion outfit generation focuses on promoting visual consistency of garments by leveraging key information from reference image and text prompt. However, t…

cs.CV2026

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Haiwen Diao, Penghao Wu, Hanming Deng +55

Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fra…