14 citations · 38 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
Training-Free Exponential Context Extension via Cascading KV Cache
Jeffrey Willette, Heejun Lee, Youngwan Lee +2
The transformer's context window is vital for tasks such as few-shot learning and conditional generation as it preserves previous tokens for active memory. However, as the context…
A Training-free Sub-quadratic Cost Transformer Model Serving Framework With Hierarchically Pruned Attention
Heejun Lee, Geon Park, Youngwan Lee +7
In modern large language models (LLMs), increasing the context length is crucial for improving comprehension and coherence in long-context, multi-modal, and retrieval-augmented lan…
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…