BLIP3o-NEXT: Next Frontier of Native Image Generation

📌 核心贡献

BLIP3o-NEXT是BLIP3系列中一个完全开源的基础模型，将文本到图像生成和图像编辑统一在一个架构中，展示了强大的生成和编辑能力。该研究发现，模型的性能主要取决于可扩展性和推理速度，并通过强化学习进一步提升了原生图像生成的效果。

📖 摘要

We present BLIP3o-NEXT, a fully open-source foundation model in the BLIP3 series that advances the next frontier of native image generation. BLIP3o-NEXT unifies text-to-image generation and image editing within a single architecture, demonstrating strong image generation and image editing capabilities. In developing the state-of-the-art native image generation model, we identify four key insights: (1) Most architectural choices yield comparable performance; an architecture can be deemed effective provided it scales efficiently and supports fast inference; (2) The successful application of reinforcement learning can further push the frontier of native image generation; (3) Image editing still remains a challenging task, yet instruction following and the consistency between generated and reference images can be significantly enhanced through post-training and data engine; (4) Data quality and scale continue to be decisive factors that determine the upper bound of model performance. Building upon these insights, BLIP3o-NEXT leverages an Autoregressive + Diffusion architecture in which an autoregressive model first generates discrete image tokens conditioned on multimodal inputs, whose hidden states are then used as conditioning signals for a diffusion model to generate high-fidelity images. This architecture integrates the reasoning strength and instruction following of autoregressive models with the fine-detail rendering ability of diffusion models, achieving a new level of coherence and realism. Extensive evaluations of various text-to-image and image-editing benchmarks show that BLIP3o-NEXT achieves superior performance over existing models.

🔍 关键信息

字段	内容
机构	Salesforces
发表	2025-10-17
分类	cs.CV
链接	arXiv

📝 我的笔记

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