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20242026
most citedLumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining

2 citations · 3 across the 12 of their papers we have counts for

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cs.CV2025★ 1 cited

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer

Image Team, Huanqia Cai, Sihan Cao +21

The landscape of high-performance image generation models is currently dominated by proprietary systems, such as Nano Banana Pro and Seedream 4.0. Leading open-source alternatives,…

cs.CV2025

Distribution Matching Distillation Meets Reinforcement Learning

Dengyang Jiang, Dongyang Liu, Zanyi Wang +12

Distribution Matching Distillation (DMD) facilitates efficient inference by distilling multi-step diffusion models into few-step variants. Concurrently, Reinforcement Learning (RL)…

cs.CV2025

Lumina-mGPT 2.0: Stand-Alone AutoRegressive Image Modeling

Yi Xin, Juncheng Yan, Qi Qin +18

We present Lumina-mGPT 2.0, a stand-alone, decoder-only autoregressive model that revisits and revitalizes the autoregressive paradigm for high-quality image generation and beyond.…

cs.CV2025

OmniCaptioner: One Captioner to Rule Them All

Yiting Lu, Jiakang Yuan, Zhen Li +17

We propose OmniCaptioner, a versatile visual captioning framework for generating fine-grained textual descriptions across a wide variety of visual domains. Unlike prior methods lim…

cs.CV2025

Lumina-Image 2.0: A Unified and Efficient Image Generative Framework

Qi Qin, Le Zhuo, Yi Xin +20

We introduce Lumina-Image 2.0, an advanced text-to-image generation framework that achieves significant progress compared to previous work, Lumina-Next. Lumina-Image 2.0 is built u…

cs.CV2025

LeX-Art: Rethinking Text Generation via Scalable High-Quality Data Synthesis

Shitian Zhao, Qilong Wu, Xinyue Li +10

We introduce LeX-Art, a comprehensive suite for high-quality text-image synthesis that systematically bridges the gap between prompt expressiveness and text rendering fidelity. Our…

cs.CV2025

Lumina-Video: Efficient and Flexible Video Generation with Multi-scale Next-DiT

Dongyang Liu, Shicheng Li, Yutong Liu +16

Recent advancements have established Diffusion Transformers (DiTs) as a dominant framework in generative modeling. Building on this success, Lumina-Next achieves exceptional perfor…