43 citations · 103 across the 17 of their papers we have counts for
18 papers
MultiVerse: A Multi-Turn Conversation Benchmark for Evaluating Large Vision and Language Models
Young-Jun Lee, Byung-Kwan Lee, Jianshu Zhang +9
Vision-and-Language Models (VLMs) have shown impressive capabilities on single-turn benchmarks, yet real-world applications often demand more intricate multi-turn dialogues. Existi…
Intriguing Properties of Large Language and Vision Models
Young-Jun Lee, Byungsoo Ko, Han-Gyu Kim +2
Recently, large language and vision models (LLVMs) have received significant attention and development efforts due to their remarkable generalization performance across a wide rang…
Stark: Social Long-Term Multi-Modal Conversation with Persona Commonsense Knowledge
Young-Jun Lee, Dokyong Lee, Junyoung Youn +4
Humans share a wide variety of images related to their personal experiences within conversations via instant messaging tools. However, existing works focus on (1) image-sharing beh…
VVS: Video-to-Video Retrieval with Irrelevant Frame Suppression
Won Jo, Geuntaek Lim, Gwangjin Lee +3
In content-based video retrieval (CBVR), dealing with large-scale collections, efficiency is as important as accuracy; thus, several video-level feature-based studies have actively…
Group Generalized Mean Pooling for Vision Transformer
Byungsoo Ko, Han-Gyu Kim, Byeongho Heo +4
Vision Transformer (ViT) extracts the final representation from either class token or an average of all patch tokens, following the architecture of Transformer in Natural Language…
DialogCC: An Automated Pipeline for Creating High-Quality Multi-Modal Dialogue Dataset
Young-Jun Lee, Byungsoo Ko, Han-Gyu Kim +2
As sharing images in an instant message is a crucial factor, there has been active research on learning an image-text multi-modal dialogue models. However, training a well-generali…