3 papers
cs.CV2026
GMAIL: Generative Modality Alignment for generated Image Learning
Shentong Mo, Sukmin Yun
Generative models have made it possible to synthesize highly realistic images, potentially providing an abundant data source for training machine learning models. Despite the advan…
cs.CV2024
Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs
Sukmin Yun, Haokun Lin, Rusiru Thushara +14
Multimodal large language models (MLLMs) have shown impressive success across modalities such as image, video, and audio in a variety of understanding and generation tasks. However…
cs.CV2024
DMT-JEPA: Discriminative Masked Targets for Joint-Embedding Predictive Architecture
Shentong Mo, Sukmin Yun
The joint-embedding predictive architecture (JEPA) recently has shown impressive results in extracting visual representations from unlabeled imagery under a masking strategy. Howev…