46 citations · 46 across the 6 of their papers we have counts for
4 papers · 1 filter
DiffFluid: Plain Diffusion Models are Effective Predictors of Flow Dynamics
Dongyu Luo, Jianyu Wu, Jing Wang +3
We showcase the plain diffusion models with Transformers are effective predictors of fluid dynamics under various working conditions, e.g., Darcy flow and high Reynolds number. Unl…
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…
EMR-Merging: Tuning-Free High-Performance Model Merging
Chenyu Huang, Peng Ye, Tao Chen +3
The success of pretrain-finetune paradigm brings about the release of numerous model weights. In this case, merging models finetuned on different tasks to enable a single model wit…
ChemLLM: A Chemical Large Language Model
Di Zhang, Wei Liu, Qian Tan +12
Large language models (LLMs) have made impressive progress in chemistry applications. However, the community lacks an LLM specifically designed for chemistry. The main challenges a…