2 citations · 3 across the 4 of their papers we have counts for
4 papers
Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation
Kartar Kumar, Rajesh Kumar, Nikesh Lagun
Large language models (LLMs) are beginning to reshape how organic-synthesis workflows are represented, queried, planned, and connected to experimental automation. Assessing their c…
MediQ-GAN: Quantum-Inspired GAN for High Resolution Medical Image Generation
Qingyue Jiao, Yongcan Tang, Jun Zhuang +2
Machine learning-assisted diagnosis shows promise, yet medical imaging datasets are often scarce, imbalanced, and constrained by privacy, making data augmentation essential. Classi…
IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation
Xinchen Zhang, Ling Yang, Guohao Li +6
Advanced diffusion models like RPG, Stable Diffusion 3 and FLUX have made notable strides in compositional text-to-image generation. However, these methods typically exhibit distin…
RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models
Xinchen Zhang, Ling Yang, Yaqi Cai +8
Diffusion models have achieved remarkable advancements in text-to-image generation. However, existing models still have many difficulties when faced with multiple-object compositio…