6 citations · 6 across the 5 of their papers we have counts for
6 papers
Reason in the Words You Speak: Idiolectal Paraphrasing Off-Policy Traces for Reasoning Distillation in VideoLLMs
Ji Soo Lee, Jinyoung Park, Seohyun Lee +4
Recent large language models achieve strong performance on complex reasoning tasks, where reinforcement learning with Group Relative Policy Optimization (GRPO) has emerged as a lea…
DocPrune:Efficient Document Question Answering via Background, Question, and Comprehension-aware Token Pruning
Joonmyung Choi, Sanghyeok Lee, Jongha Kim +4
Recent advances in vision-language models have demonstrated remarkable performance across diverse multi-modal tasks, including document question answering that leverages structured…
Representation Shift: Unifying Token Compression with FlashAttention
Joonmyung Choi, Sanghyeok Lee, Byungoh Ko +3
Transformers have demonstrated remarkable success across vision, language, and video. Yet, increasing task complexity has led to larger models and more tokens, raising the quadrati…
EfficientViM: Efficient Vision Mamba with Hidden State Mixer based State Space Duality
Sanghyeok Lee, Joonmyung Choi, Hyunwoo J. Kim
For the deployment of neural networks in resource-constrained environments, prior works have built lightweight architectures with convolution and attention for capturing local and…
Multi-criteria Token Fusion with One-step-ahead Attention for Efficient Vision Transformers
Sanghyeok Lee, Joonmyung Choi, Hyunwoo J. Kim
Vision Transformer (ViT) has emerged as a prominent backbone for computer vision. For more efficient ViTs, recent works lessen the quadratic cost of the self-attention layer by pru…
vid-TLDR: Training Free Token merging for Light-weight Video Transformer
Joonmyung Choi, Sanghyeok Lee, Jaewon Chu +2
Video Transformers have become the prevalent solution for various video downstream tasks with superior expressive power and flexibility. However, these video transformers suffer fr…