Delighted to have our Auto-Context method adopted in the Nobel prize winning AlphaFold work. Auto-Context Illustration Figure below from pages.ucsd.edu/~ztu/publicati…

We’re thrilled that our lab’s work on “Deeply-Supervised Nets” has received the Test-of-Time Award at AISTATS 2025! 🏆 This prestigious award honors papers published 10 years ago that have had a lasting and significant impact on the field of artificial intelligence and

Check out our #ICCV2025 paper Lay-Your-Scene! We introduce a controllable and lightweight diffusion transformer architecture for natural scene layout generation and propose a comprehensive benchmark for evaluating layout quality. Website: mlpc-ucsd.github.io/Lay-Your-Scene/ Paper:

📄 Excited to present our ICCV paper "YOLO-Count: Differentiable Object Counting for Text-to-Image Generation!"⁣ 🎯 We show a new regression objective that boosts both counting accuracy and controllability in T2I models.⁣ 📍 Poster #1545, Wed 2:45PM, Exhibit Hall I⁣ #ICCV2025