1 citations · 2 across the 8 of their papers we have counts for
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MultihopSpatial: Multi-hop Compositional Spatial Reasoning Benchmark for Vision-Language Model
Youngwan Lee, Soojin Jang, Yoorhim Cho +3
Spatial reasoning is foundational for Vision-Language Models (VLMs), particularly when deployed as Vision-Language-Action (VLA) agents in physical environments. However, existing b…
HoliSafe: Holistic Safety Benchmarking and Modeling for Vision-Language Model
Youngwan Lee, Kangsan Kim, Kwanyong Park +5
Despite emerging efforts to enhance the safety of Vision-Language Models (VLMs), current approaches face two main shortcomings. 1) Existing safety-tuning datasets and benchmarks on…
VideoICL: Confidence-based Iterative In-context Learning for Out-of-Distribution Video Understanding
Kangsan Kim, Geon Park, Youngwan Lee +2
Recent advancements in video large multimodal models (LMMs) have significantly improved their video understanding and reasoning capabilities. However, their performance drops on ou…
Visualizing the loss landscape of Self-supervised Vision Transformer
Youngwan Lee, Jeffrey Ryan Willette, Jonghee Kim +1
The Masked autoencoder (MAE) has drawn attention as a representative self-supervised approach for masked image modeling with vision transformers. However, even though MAE shows bet…
KOALA: Empirical Lessons Toward Memory-Efficient and Fast Diffusion Models for Text-to-Image Synthesis
Youngwan Lee, Kwanyong Park, Yoorhim Cho +2
As text-to-image (T2I) synthesis models increase in size, they demand higher inference costs due to the need for more expensive GPUs with larger memory, which makes it challenging…