4 citations · 4 across the 6 of their papers we have counts for
3 papers · 1 filter
Physics Informed Distillation for Diffusion Models
Joshua Tian Jin Tee, Kang Zhang, Hee Suk Yoon +3
Diffusion models have recently emerged as a potent tool in generative modeling. However, their inherent iterative nature often results in sluggish image generation due to the requi…
BI-MDRG: Bridging Image History in Multimodal Dialogue Response Generation
Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee +4
Multimodal Dialogue Response Generation (MDRG) is a recently proposed task where the model needs to generate responses in texts, images, or a blend of both based on the dialogue co…
C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion
Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee +3
In deep learning, test-time adaptation has gained attention as a method for model fine-tuning without the need for labeled data. A prime exemplification is the recently proposed te…