6 citations · 22 across the 17 of their papers we have counts for
19 papers
Saliency-Aware Model Merging
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
Model merging aims to consolidate multiple task-specific models fine-tuned on different datasets into a unified architecture that performs cross-domain proficiency. Current data-fr…
V-LynX: Token Interface Alignment for Video+X LLMs
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
This study introduces an intriguing phenomenon in Video LLMs: rather than merely translating frames into textual embeddings, Video LLMs establish a continuous manifold, token inter…
Language-guided Recursive Spatiotemporal Graph Modeling for Video Summarization
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
Video summarization aims to select keyframes that are visually diverse and can represent the whole story of a given video. Previous approaches have focused on global interlinkabili…
Bootstrap Your Own Views: Masked Ego-Exo Modeling for Fine-grained View-invariant Video Representations
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
View-invariant representation learning from egocentric (first-person, ego) and exocentric (third-person, exo) videos is a promising approach toward generalizing video understanding…
Faster Parameter-Efficient Tuning with Token Redundancy Reduction
Kwonyoung Kim, Jungin Park, Jin Kim +2
Parameter-efficient tuning (PET) aims to transfer pre-trained foundation models to downstream tasks by learning a small number of parameters. Compared to traditional fine-tuning, w…
Bridging Vision and Language Spaces with Assignment Prediction
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
This paper introduces VLAP, a novel approach that bridges pretrained vision models and large language models (LLMs) to make frozen LLMs understand the visual world. VLAP transforms…