6 citations · 11 across the 7 of their papers we have counts for
7 papers
ProteinAE: Protein Diffusion Autoencoders for Structure Encoding
Shaoning Li, Le Zhuo, Yusong Wang +5
Developing effective representations of protein structures is essential for advancing protein science, particularly for protein generative modeling. Current approaches often grappl…
Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understanding
Yi Xin, Qi Qin, Siqi Luo +29
We introduce Lumina-DiMOO, an open-source foundational model for seamless multi-modal generation and understanding. Lumina-DiMOO sets itself apart from prior unified models by util…
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.…
Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers
Peng Gao, Le Zhuo, Dongyang Liu +17
Sora unveils the potential of scaling Diffusion Transformer for generating photorealistic images and videos at arbitrary resolutions, aspect ratios, and durations, yet it still lac…
Lumina-Next: Making Lumina-T2X Stronger and Faster with Next-DiT
Le Zhuo, Ruoyi Du, Han Xiao +19
Lumina-T2X is a nascent family of Flow-based Large Diffusion Transformers that establishes a unified framework for transforming noise into various modalities, such as images and vi…
ProtLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training
Le Zhuo, Zewen Chi, Minghao Xu +5
We propose ProtLLM, a versatile cross-modal large language model (LLM) for both protein-centric and protein-language tasks. ProtLLM features a unique dynamic protein mounting mecha…