11 papers
RepFusion: Leveraging Multimodal Priors for Denoising in Representation Space
Xichen Pan, Aashu Singh, Satya Narayan Shukla +3
Large language models (LLMs) are widely used in text-to-image (T2I) systems, but they are typically limited to text encoding, while denoising is handled by newly trained generative…
Cambrian-P: Pose-Grounded Video Understanding
Jihan Yang, Zifan Zhao, Xichen Pan +6
Camera pose matters. The position and orientation of each viewpoint define a shared spatial coordinate frame that relates observations across video frames. Yet this signal is large…
V-Co: A Closer Look at Visual Representation Alignment via Co-Denoising
Han Lin, Xichen Pan, Zun Wang +4
Pixel-space diffusion has recently re-emerged as a strong alternative to latent diffusion, enabling high-quality generation without pretrained autoencoders. However, standard pixel…
Think Then Embed: Generative Context Improves Multimodal Embedding
Xuanming Cui, Jianpeng Cheng, Hong-you Chen +11
There is a growing interest in Universal Multimodal Embeddings (UME), where models are required to generate task-specific representations. While recent studies show that Multimodal…
Exploring MLLM-Diffusion Information Transfer with MetaCanvas
Han Lin, Xichen Pan, Ziqi Huang +10
Multimodal learning has rapidly advanced visual understanding, largely via multimodal large language models (MLLMs) that use powerful LLMs as cognitive cores. In visual generation,…
BLIP3o-NEXT: Next Frontier of Native Image Generation
Jiuhai Chen, Le Xue, Zhiyang Xu +12
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 gener…