4 papers
Nexus-Gen: Unified Image Understanding, Generation, and Editing via Prefilled Autoregression in Shared Embedding Space
Hong Zhang, Zhongjie Duan, Xingjun Wang +6
Unified multimodal generative models aim to integrate image understanding and generation abilities, offering significant advantages in harnessing multimodal corpora, particularly i…
Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs
Tiancheng Gu, Kaicheng Yang, Ziyong Feng +6
The Contrastive Language-Image Pre-training (CLIP) framework has become a widely used approach for multimodal representation learning, particularly in image-text retrieval and clus…
EliGen: Entity-Level Controlled Image Generation with Regional Attention
Hong Zhang, Zhongjie Duan, Xingjun Wang +2
Recent advancements in diffusion models have significantly advanced text-to-image generation, yet global text prompts alone remain insufficient for achieving fine-grained control o…
Minimum Tuning to Unlock Long Output from LLMs with High Quality Data as the Key
Yingda Chen, Xingjun Wang, Jintao Huang +3
As large language models rapidly evolve to support longer context, there is a notable disparity in their capability to generate output at greater lengths. Recent study suggests tha…