4 citations · 6 across the 11 of their papers we have counts for
4 papers · 1 filter
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…
Large Language Models can Share Images, Too!
Young-Jun Lee, Dokyong Lee, Joo Won Sung +2
This paper explores the image-sharing capability of Large Language Models (LLMs), such as GPT-4 and LLaMA 2, in a zero-shot setting. To facilitate a comprehensive evaluation of LLM…
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…